Signal loss was detected within tumors at both time points post USPIO. Images acquired at 4 days demonstrated signal loss encompassing the entire tumor and around the periphery at 3 weeks. Number of black voxels suggested higher numbers of TAMs in the tumor at the later time point. After PFC administration, Fluorine-19 (19F) signal was detected in a similar spatial distribution as signal loss post USPIO. 19F signal quantification revealed that the number of 19F spins was not significantly different at the two time points, suggesting a similar number of TAMs were present in tumors but accumulated in different regions. 19F signal was higher centrally in tumors at 4 days and heterogenous around the periphery at 3 weeks. This study revealed that 19F-based cell tracking methods better represent TAM density and provides additional information not achievable with iron-based methods.Tumor associated macrophages (TAMs) are associated with tumor growth and metastasis. MRI can detect TAMs labeled with iron oxide (USPIO) or perfluorocarbon (PFC) agents. This study compared these two cell tracking approaches for imaging TAMs  Inflammation is a key determinant in cancer behavior, playing a pivotal role in cancer initiation and progressionIn breast cancer, TAMs have been linked to increased metastasis, angiogenesis and tumor aggressiveness2in vivo would add tremendously to our understanding of the spatial and temporal changes of this cell population in the tumor microenvironment.Most studies of TAMs in breast cancer are performed using histology; a number of these approaches have been reviewedin vivo cellular MRI techniques. To do this, iron nanoparticles are administered intravenously (i.v.) and are subsequently internalized by monocytes/macrophages in the reticuloendothelial system . In the presence of an inflammatory condition, iron nanoparticles are taken up by associated macrophages and accumulate in the affected organ/tissue. MRI is typically performed one day after the administration of iron, to allow time for the accumulation of labeled cells and to permit clearance of intravascular ironin vivo labeling efficiency of macrophages is dependent upon many factors including macrophage polarization and the type of nanoparticle used ; not all macrophages become labeled. However, most of these studies use ultra-small superparamagnetic iron oxide (USPIO) agents, which are smaller and have longer circulation times compared to larger iron oxide agents, leading to greater uptake. Areas which contain iron-labeled inflammatory cells appear as regions of low signal intensity in iron sensitive MR images. This approach has been used to image inflammation in many diseases including atherosclerosis7Macrophages can be imaged using 19F) imaging agent is a newly emerging technique for MRI cell tracking. 19F-based cell tracking of macrophages is achieved through the administration of perfluorocarbons (PFCs), which are phagocytosed in vivo by macrophages, similar to the uptake of iron nanoparticles previously described. 19F MRI addresses some of the limitations associated with iron-labeled cell tracking. First, there is no MRI detectable fluorine in the native tissue, which allows for high specificity. Second, in contrast to the indirect visualization of iron-labeled cells by observed signal loss, the spins of 19F nuclei are directly detected and 19F signal is proportional to the number of 19F spins per voxel.The use of a fluorine-19  present challenges due to the low 19F concentrations in vivo. The current cellular detection sensitivity for 19F MRI is estimated to be on the order of thousands of 19F labeled cells per voxel. Where there are lower numbers of labeled cells, they may not be detected and therefore there is a risk of underestimating cell number. 19F-based cell tracking methods have been applied to detect and monitor inflammation in a variety of experimental models including arthritis1621232419F-based MRI for the identification and quantification of TAMs in a mouse model of breast cancer.The main limitation of 2 in Dulbecco’s Modified Eagle’s Medium-high glucose media  supplemented with 10% fetal bovine serum and passaged every 2–3 days.4T1 murine breast cancer cells  were chosen due to their known TAM contentth mammary fat pad. The injection site was monitored daily. For iron-based imaging, 0.5 mmol/kg Ferahame  was injected via tail vein 24 hours before post iron imaging. For fluorine-based imaging, mice were administered 200 μl (~7.8E19 19F atoms in 1 ml) PFC agent  via the tail vein 48 hours prior to imaging. This PFC has a red fluorescent tag (Texas Red). Animals were observed until alert and active, when they were returned to their cages.Female BALB/c mice  were obtained and cared for in accordance with the standards of the Canadian Council on Animal Care, under an approved protocol by the Animal Use Subcommittee of Western University’s Council on Animal Care. Mice (n = 20) were anesthetized with isoflurane administered at 2% in oxygen followed by an injection of 300,000 4T1 cells  suspended in 50 μl Hanks balanced salt solution (HBSS) into the 4In vivo proton (1H) and 19F MRI were performed at two time points: (1) when the tumor was first palpable (imaged at 4 days) and (2) at 3 weeks post cancer cell implantation. While imaging, mice were anesthetized with 2% isoflurane in oxygen. USPIO imaging : Images were obtained pre and 24 hours post i.v. USPIO on a 3 Tesla (T) GE clinical MR system  equipped with a custom built insertable gradient coil (maximum gradient strength 500 mT/m and peak slew rate 3000 T/m/s) and using a solenoidal mouse body radiofrequency (RF) coil. A 3D balanced steady state free precession (bSSFP) imaging sequence was used to obtain high resolution 1H images of the whole mouse body. Image resolution was 200 × 200 × 200 μm and sequence parameters were as follows: FOV = 60 × 30 mm, matrix = 300 × 150, flip angle = 35°, bandwidth = 31 kHz, TR/TE = 6.3/3.1 ms, 2 averages and 8 phase cycles resulting in a scan time of ~30 minutes. PFC imaging : 1H and 19F images were acquired 48 hours post PFC with a 9.4 T Varian small animal MRI system using a custom built dual 1H/19F birdcage coil, tuned to 400.2 MHz for proton and 376.8 MHz for 19F imaging. A higher magnetic field was used for 19F imaging due to the lower detection sensitivity. Reference tubes of known 19F concentration (3.33 × 1016 19F/μl) were placed alongside the mouse for quantification purposes. 1H and 19F images were acquired with a bSSFP sequence. 1H images were acquired with 200 × 200 × 200 μm spatial resolution and the following parameters: FOV = 50 × 36 × 36 mm, matrix = 250 × 180 × 180, flip angle = 30°, bandwidth = 87 kHz, TR/TE = 3.9/1.9 ms, 3 averages and 4 phase cycles with a scan time of ~20 minutes. 19F images were acquired with 500 × 500 × 1000 μm spatial resolution with the following parameters: FOV = 50 × 36 × 36 mm, matrix = 100 × 72 × 36, flip angle = 70°, bandwidth = 25 kHz, TR/TE = 5.5/2.8 ms, 30 averages and 4 phase cycles resulting in a scan time of ~35 minutes. Excitation was performed with a 1 kHz gauss pulse to prevent detection of isoflurane.Mice were euthanized via intraperitoneal injection of sodium pentobarbital  immediately following the last MR exam. The tumors from mice that received USPIO were excised and placed in 4% formalin for fixation. Tumors were paraffin embedded, sectioned (6 μm) and subsequently stained with hematoxylin and eosin (H&E), Perls’ Prussian Blue (PPB) for iron and biotinylated isolectin B4 (Sigma Adrich) which binds to the galactose-type terminal present on activated macrophages. Mice that received PFC were transcardially perfused with saline followed by 4% paraformaldehyde (PFA) to reduce autofluorescence within specimens. Tumors were excised and cryoprotected by passage through a sucrose gradient of 10%, 20% and 30% for 24 hours each. Samples were then frozen in an OCT compound and cryostat sections were collected (10 μm). Diaminobenzidine (DAB) and fluorescent immunohistochemistry (IHC) was performed for lectin and fluorescent images were collected to detect the red-fluorescence from the PFC agent.Microscopy was performed using a Zeiss Axio Imager A1 microscope  equipped with a Retiga EXi  digital camera. The use of a slide scanner  allowed for digital whole tumor section scanning (0.5 μm resolution).PFC Imaging:19F images were overlaid onto the proton images to determine where the 19F signal was located within the mouse. From 19F images, voxels containing 19F signal which were within the tumor were manually delineated and 19F quantification was performed using VoxelTracker software . In brief, the total number of 19F spins were determined by comparing the sum of the 19F signal within a region of interest to the signal generated by reference tubes containing a known amount of 19F spins (3.33 × 1016 19F/μl) and taking into consideration signal from noise.Analysis of signal loss in tumor images was performed using OsiriX imaging software . Pre and post iron images were compared to detect regions of signal loss that were present within tumors post USPIO. Tumors were manually outlined slice by slice in post iron images, creating a 3D tumor volume. The total number of black voxels per tumor  was then determined from these volumes by setting a threshold. The threshold was chosen by measuring the mean signal intensity +2 standard deviations from within the signal void region. Then the total number of black voxels with signal intensity values below this threshold value was obtained from the tumor histogram. The 3D isotropic voxels allowed multi-planar reformatting to compare the spatial distribution of PPB staining of a whole tumor section to signal loss on MR images. p < 0.05 was considered a significant finding.Statistical analyses were performed using GraphPad Prism software . Data are expressed as mean ± SD. Unpaired, two-tailed t-tests were performed on quantification between time points, within imaging method; 3 and the region of signal loss covered the entire tumor volume. For mice imaged at 3 weeks post cell implantation the regions of signal loss were mainly in the periphery and not within the central region of the tumor. Tumors were significantly larger at this stage; the mean tumor volume was 534 mm3. Representative images acquired post USPIO are shown in All mice developed 4T1 mammary fat pad tumors. Images of mice that received USPIO showed regions of signal hypointensity within the tumors. For mice that were injected on day 3 post cell implantation and imaged on day 4, tumors were relatively small; the mean tumor volume was 26.7 mm19F MRI images were created by an overlay of hydrogen (1H) and 19F MR datasets  in the number of TAMs at 3 weeks compared to 4 days. For post PFC imaging the number of 19F spins was determined for each tumor volume, presented as mean values and standard deviation for each time point (p = 0.4614) in TAMs between the two time points.For post USPIO images the signal loss was quantified by measuring the number of black voxels for each tumor volume, presented as mean values and standard deviation for each time point . This anme point . AnalysiPPB staining for iron in tumors showed good spatial correspondence with MRI. Representative PPB staining for tumors at each time point is shown in 19F-based MRI signal detection was validated using fluorescence microscopy for macrophage staining and detection of the red fluorescent PFC. 19F-based MRI methods for imaging TAMs. To the best of our knowledge, this is the first time these two imaging approaches have been compared for TAM detection in the same cancer model. Two different MRI systems were utilized for these methods. Proton images for detection of signal loss due to iron-labeled cells were acquired using a 3 T clinical MRI system along with a custom built insertable gradient coil which permits high resolution imaging of mice on a human sized scanner. 19F images were acquired using a 9.4 T dedicated small animal MRI system to boost SNR as a way to compensate for decreased detection sensitivity.In this study we have assessed iron-based and et al. showed that TAMs, myeloid derived suppressor cells (MDSC) and regulatory T cells dominated the early response, and persisted as tumors became more invasive, in a model of pancreatic ductal carcinomaBoth imaging methods revealed the early presence of TAMs, when tumors were first palpable. Although the dynamics of immune cell infiltration in tumors is not well understood, several histology-based studies have observed a pronounced immune cell infiltration in very early, low-grade pre-invasive tumors. Clark 19F-based cellular MRI methods to visualize TAMs in various cancer models and at various time points. One study injected iron nanoparticles on day 5 and used MRI to follow TAMs during growth of implanted tumor fragments719F MRI to image macrophages associated with cancer. In a pilot study which detected 19F signal in a 4T1 tumor at one week post cancer cell injection, 19F signal due to macrophage uptake was observed within the outer margin of the tumor, thought to be contributing to the invasive front of the tumorBoth imaging methods we used showed the same spatial distribution of TAMs at each time point; throughout the entire tumor at 4 days and restricted to the periphery at 3 weeks. Past studies have used both iron and The anti-tumor or pro-tumor activity of TAMs may depend on their localization within cancer tissue3119F signal, attributed to PFC-positive TAMs, indicated that the total number of 19F spins was not different in the small, early tumors compared to the larger tumors imaged at 3 weeks post cell injection. This result suggests the number of TAMs doesn’t change much during tumor development over this time period but that the location of the TAMs is altered. An in vivo murine study of TAMs has suggested they have a long life span (ie. at least 4–5 weeks) and although there is likely some turnover, this may be offset by local proliferation and monocyte infiltrationQuantification of the signal measured by each imaging technique produced different results. The quantification of 19F agent functions like a tracer in that 19F MRI directly detects the 19F nuclei that are associated with the labeled cells; the 19F signal is directly proportional to the number of 19F spins. Maps of the number of 19F spins in tumors provided additional information on TAM distribution, revealing a higher number of 19F spins (pink) in the central region of tumors imaged at 4 days post cell injection and a heterogeneous pattern of 19F spins around the periphery of tumors imaged at 3 weeks. We believe these methods will allow for longitudinal monitoring of the density and distribution of TAMs in the same subjects, which could provide valuable information on TAM localization and accumulation over time.Unlike iron particles, which are detected through their indirect effects on the surrounding water protons, the et al. compared four quantitative methods for quantification of iron-labeled cells transplanted into mouse brain: (1) T2 relaxometry, (2) T2* relaxometry, (3) the volume of the cloverleaf hypointense artifact generated on T2*-weighted images, and (4) the volume of the cloverleaf hyperintense artifact generated on positive contrast imagesThe quantification of signal loss, attributed to iron-positive TAMs, suggested that TAM infiltration was greater in larger tumors imaged at 3 weeks post cell implantation compared to early tumors imaged at day 4. Quantifying signal loss, however, is not straightforward because the relationship between signal loss and iron concentration is not linear and because the presence of iron produces a localized disruption to the magnetic field homogeneity, resulting in a region of signal loss that extends far beyond the actual boundary of the cells. This is a susceptibility related artifact, known as the blooming effectin vitro calibration curvesOther studies have used relaxometry to quantify signal loss due to iron-labeled cells. With multi-gradient echo imaging T2 or T2* relaxation can be measured and T2/T2* maps generated to show the distribution of iron-labeled cells in tumors. Although relaxometry data allows for a direct estimate of cell number, these studies have only shown fair agreement between the number of injected cells and the number estimated from T2 quantification and 19F-based cell tracking does have some limitations when imaging TAMs. Compared to iron-based methods, the detection sensitivity for labeled cells is much lower for 19F. 19F MRI cell tracking likely underestimates the cell density in the tumor because of the low detection sensitivity; thousands of cells per voxel are required for detection of PFC-labeled cells, whereas single iron-labeled cells can be detected3719F labeled cells, only the number of 19F spins within the ROI. Quantification of cell number can only be determined in experiments where PFC is used to pre-label cells prior to implantation and the number of 19F spins per cell is known. Additional information can be determined post PFC administration if the tissues are removed and analyzed by 19F NMR. In this case, the total 19F content of the sample is determined and results normalized to tissue weight generating an “inflammation index”, expressed as the number of 19F spins per gram of tissue19F-based imaging of TAMs in individual breast tumors would allow for identification of breast tumors which are heavily infiltrated with TAMs and could be used as a biomarker for decisions about how to best treat these patients and for monitoring responses to therapy.Understanding the trafficking and timing of TAM infiltration will provide valuable insight into potential obstacles for developing anti-inflammatory treatments targeted against TAM recruitment and function that may be beneficial for both tumor prevention and therapy. How to cite this article: Makela, A. V. et al. Quantifying tumor associated macrophages in breast cancer: a comparison of iron and fluorine-based MRI cell tracking. Sci. Rep.7, 42109; doi: 10.1038/srep42109 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Vitis vinifera) is among the most ancient and prestigious wine grape varieties characterised by a wide genetic variability exhibited by a high number of clones (vegetatively propagated lines of selected mother plants). However, limited information is available for this cultivar at the molecular and genomic levels. The whole-genomes of three ‘Nebbiolo’ clones  were re-sequenced and a de novo transcriptome assembly was produced. Important remarks about the genetic peculiarities of ‘Nebbiolo’ and its intra-varietal variability useful for clonal identification were reported. In particular, several varietal transcripts identified for the first time in ‘Nebbiolo’ were disease resistance genes and single-nucleotide variants (SNVs) identified in ‘Nebbiolo’, but not in other cultivars, were associated with genes involved in the stress response. Ten newly discovered SNVs were successfully employed to identify some periclinal chimeras and to classify 98 ‘Nebbiolo’ clones in seven main genotypes, which resulted to be linked to the geographical origin of accessions. In addition, for the first time it was possible to discriminate some ‘Nebbiolo’ clones from the others.‘Nebbiolo’ ( Nevertheless, the use of next-generation sequencing data with the available grapevine reference genome PN40024 may lead to the loss of important information on the interesting characteristics of cultivars. This is due not only to the possible lack of information in the reference genome4 because of its highly homozygous nature, but also to the impossibility of the reference genome to represent the entire genetic variability of the species pangenome6. The de novo assembly of plant genomes from short-read sequencing data is challenging7 for highly complex polyploid genomes and can lead to highly fragmented genome drafts with no possibility for correctly phasing the haplotypes8. However, several projects involving the sequencing or re-sequencing of grapevine cultivars have recently been performed14. There is increasing evidence that genomic variants such as single-nucleotide variants (SNVs), small insertions and deletions (INDELs), inter- and intra-chromosomal translocations and inversions and private genes can contribute to intra-specific variability or to a dispensable genome15, unearthing phenotypic characters specific to each cultivar6.The availability of a reference genome in grapevineVitis vinifera subsp. sylvestris vines, which likely occurred at multiple geographical centres16; crosses between domesticated (maybe introduced from other areas) and local wild plants; the historic practice of growing seedlings from spontaneous crosses; and conventional breeding. The selected individuals were then multiplied by vegetative propagation , during which somatic modifications spontaneously occurred and were maintained, thus giving rise to the intra-varietal variability associated with phenotypic variation among grapevine clones17. In some cases somatic mutations affecting only some cells led to chimeras, for example periclinal chimeras resulting from mutation of only one cell layer (L1 or L2) of apical meristem. Over the years, the berry colour is a phenotypic character intensively investigated to deepen these mutations, and interesting examples derived from the ‘Pinot’ family and the mutations associated to ‘Pinot noir’, ‘Pinot gris’ and ‘Pinot blanc’19. Among the thousands of cultivars throughout the world that constitute the germplasm of V. vinifera, ‘Nebbiolo’ (major synonyms ‘Chiavennasca’ and ‘Spanna’) is among the most ancient and most prestigious wine grape varieties and is renowned for its use in producing high-quality red wines21. Although cultivated today in different regions of the world , the typical cultivation area of ‘Nebbiolo’ is limited to the hilly and mountainous areas of north-western Italy , where outstanding-quality wines such as Barolo, Barbaresco, Gattinara, and Valtellina Sforzato are produced. The first historical quotation of ‘Nebbiolo’ was in 1266 and refers to the castle of Rivoli . Between the thirteenth and fourteenth centuries, ‘Nebbiolo’ was mentioned in many other documents related to Piedmont22, and in the sixteenth century in Valtellina (Lombardy)23. Although the parentage of ‘Nebbiolo’ is unknown, great numbers of grape cultivars from these areas are closely related to ‘Nebbiolo’, suggesting its cradle is in north-western Italy or at least has had a long-lasting stay in that region24. ‘Nebbiolo’ shows great intra-varietal phenotypic polymorphism resulting in clones (each obtained by vegetative propagation of a single mother plant) with different morphological and physiological characters, such as leaf shape and size, shoot vigour and yield, soluble solids, and the phenolic content of juice at harvest24. This may be the reason for the traditional classification of ‘Nebbiolo’ into the so-called subvarieties or biotypes, such as “Lampia”, “Bolla”, “Michet” and “Picoutener”. The large intra-varietal variability is highlighted by the 44 clonal selections officially registered in the Italian National Register of Grape Varieties  for nursery propagation that are widely used.Throughout history, thousands of grape cultivars have been generated. These cultivars resulted from several processes: domestication from local wild 25. Because in recent years one of the most interesting and partially achieved objectives has been to distinguish clones within a grapevine cultivar using rapid and robust techniques, the genetic basis of phenotypic variation within ‘Nebbiolo’ was investigated via the sequencing of three ‘Nebbiolo’ certified clones: CVT 71, CVT 423, and CVT 185. The sequencing of ‘Nebbiolo’ clones and a de novo transcriptome assembly provided the dual purposes of: i) determining the genetic characteristics of ‘Nebbiolo’ using more than one clone, thus representing more accurately the genetic variability within this cultivar, and ii) identifying molecular markers able to discriminate these clonal selections.Although this large intra-varietal variability, the common fingerprinting methods based on simple sequence repeats (SSRs) markers cannot discriminate clones within ‘Nebbiolo’V. vinifera cv. Nebbiolo was performed on three clones of different geographical origins and phenotypic characteristics in order to provide an outline of the genetic intra-varietal variability of ‘Nebbiolo’. Clone CVT 71, which belongs to biotype “Michet”, is characterised by medium-high vegetative vigour and yield and good environmental stability. Clone CVT 185 is of biotype “Lampia” and was selected from vineyards located in southern Piedmont, as was CVT 71. CVT 185 is characterised by medium vegetative vigour, yield, and environmental stability. Clone CVT 423 (biotype “Picoutener”), which originated from the Aosta Valley, exhibits low vegetative vigour and yield and medium-low environmental stability  per clone, obtaining about 80 Gb of sequences representing as raw sequencing reads an average of 59-fold base coverage for of each clone Table . After qde novo transcriptome characterization of ‘Nebbiolo’, RNA-Seq analysis was performed using a variety of different tissues across several developmental stages collected from the clone CVT 71 , which is in accordance with the PN40024 V1 gene annotation . Of the 44,961 putative transcripts, 26,638 aligned to the genome and integrated into the PN40024 V1 gene annotation, enabling the update of 12,361 gene structures and the detection of 325 new unannotated loci. When comparing the new loci to the annotation of PN40024 reported by Vitulo et al.4 (referred to as V2) and to the ‘Tannat’ and ‘Corvina’ transcriptomes, we found that 159 of these loci were not shared with any other cultivar , to the available V. vinifera ESTs and full-length cDNAs, and to the ‘Tannat’ and ‘Corvina’ assembled transcriptomes. One thousand nine hundred ninety-four transcripts previously unidentified in grape cultivars were identified  were shared by all three ‘Nebbiolo’ clones Table , includid Figure . The impd Figure . In thisd Figure . In addid Figure , and 34 d Figure . Indeed,d Figure  inducing® probes for genotyping assays. The allelic combination for the Ne_SNVC075 observed in the three sequenced ‘Nebbiolo’ clones (A/A) was confirmed in several ‘Nebbiolo’ clones analysed  were confirmed Table , and fored Table . In addied Table .Figure 4In addition to SNVs shared among the three clones, 28,870 SNVs showed a specific genotype in one of the three ‘Nebbiolo’ clones Table . We reta® probes in correspondence of the mutation was evaluated. After validation by Sanger sequencing, five SNVs specific to clone CVT 423, three SNVs specific to CVT 185, and three to CVT 71  and berry flesh (originated only from L2 layer) profiles. For seven SNVs no difference was observed in the allelic calls between berry skin and berry flesh in all the three sequenced clones. Conversely, the clone CVT 185 in correspondence to Ne_SNV31, Ne_SNV33 and Ne_SNV62 showed clearly different allelic calls in berry skin/leaf and berry flesh . Second, the remaining SNVs were reviewed by analysing the 300–500-bp region including the SNV and excluding the SNV when the interested region had multiple hits on the genome. Third, the feasibility of designing TaqMan71 Table  were foua Figure . In ordeh Figure . For theh Figure . This cah Figure . These r27, and the results confirmed that all selected accessions were the true-to-type Nebbiolo cultivar.The 10 SNV assays were then tested on 98 ‘Nebbiolo’ accessions collected from typical geographical areas of ‘Nebbiolo’ cultivation: southern Piedmont (Langhe and Roero), the Turin hillside, northern Piedmont , the lower Aosta Valley, and northern Lombardy  Table . Among tThe 98 ‘Nebbiolo’ clones were grouped into seven genotypes (from A to G) based on the analysis of 10 SNV markers, and in particular, only six SNVs could sufficiently discriminate the seven genotypes Fig. . Each geThe genetic relationships among ‘Nebbiolo’ genotypes were examined using both an unweighted pair-group method using arithmetic average (UPGMA) dendrogram and a median network diagram by two cluster analyses Fig. . In the A clear distribution of the certified clones , values were higher than those reported for the genomes of ‘Tannat’5 and ‘Thompson seedless’10, suggesting higher levels of mutations, heterozygosity, and hypothetically higher diversity between parental haplotypes in ‘Nebbiolo’.The high complexity of plant genomes, including the extent of repetitive content and high heterozygosity rates in diploid and polyploid genomes, make the de novo assembly of the transcriptome of one ‘Nebbiolo’ clone, was to determine the genetic characteristics typical of the ‘Nebbiolo’ variety in order to identify ‘specific’ mutations and genes of this cultivar, taking into account the intra-varietal variability.One of our main objectives, which was made possible via the sequencing of three ‘Nebbiolo’ clones and the The comparison of the transcripts assembled for ‘Nebbiolo’ CVT 71 with the PN40024 V1 and V2 genome annotations allowed the identification of 159 novel loci expressed in ‘Nebbiolo’ but not previously annotated in grape. There were 2,180 transcripts not shared with any other previously annotated cultivar, as no representative could be found in PN40024 gene space or in ‘Tannat’ and ‘Corvina’ transcriptomes. These transcripts were new discoveries and could be considered specific to the ‘Nebbiolo’ cultivar. Nevertheless, the definitions of ‘Nebbiolo-specific’ or ‘varietal genes’ were used in this context only to simplify the concept, as there are thousands of different cultivars of grapevine spread throughout the world, and these transcripts could theoretically be found in other cultivars in addition to ‘Nebbiolo’. Indeed, the comparison with ‘Tannat’ and ‘Corvina’ clearly showed that cultivar-specific genes should be reconsidered every time the transcriptome of a different variety is produced. The validation by Sanger sequencing of nine novel transcripts (only for one transcript we did not observe any amplification in ‘Nebbiolo’) confirmed the high level of reliability of the transcriptome assembly. In addition, the expression of these genes in ‘Nebbiolo’ tissues collected in different vineyards, clones and years, and at the same time the absence in PN40024 and in ‘Barbera’ cultivated near to ‘Nebbiolo’ in the same vineyard Figure , support8. Considering the SNVs shared among the three ‘Nebbiolo’ clones, excluding the point mutations retrieved in the genomes of ‘Corvina’ and ‘Tannat’, we identified 6,262 genes potentially influenced by putative ‘Nebbiolo’-specific mutations. As reported above for the ‘Nebbiolo’ transcripts, also the definition of putative ‘Nebbiolo-specific’ SNVs was used in this context only to simplify the concept, as these SNVs could theoretically be found in other cultivars in addition to ‘Nebbiolo’. However, expanding on the analysis of one of these SNVs  and in the levels of gene transcription (mutations in the promoters)32. For instance, many genes associated with SNVs belong to specific functional categories, in particular, responses to pathogens  than other cultivars such as ‘Barbera’ and ‘Pinot’, showing low FDp titres and less symptoms37. However, the presence of these mutations could suggest in addition a deficiency in the reference genome, particularly with respect to these genes. Indeed, the reference genome showed some limitations, as PN40024 was essentially derived only from two cultivars (‘Pinot noir’ and ‘Helfensteiner’) and several cycles of self-fertilisation, which was undertaken to increase its level of homozygosity1; this phenomenon probably led to the loss of particular allelic variants. The resistance to stress may be among the most polymorphic and variable functional categories in grapevine and is probably under-represented in the reference genome. This further strengthens the awareness that the reference genome does not cover all the genetic variability present not only within the genus Vitis but also within the V. vinifera species4.To characterise the ‘Nebbiolo’ genome, we essentially focussed on SNV identification, as short-read sequencing in some case has not been proven to be reliable in capturing the complex structural differences characterising the different grape cultivarsens Fig. . Similarens Fig. , and prees Table  and S7 b27, have rarely been observed among different clones of a cultivar40. Other molecular markers have been applied for distinguishing grapevine clones, such as inter-single sequence repeat (ISSR), amplified fragment length polymorphism (AFLP), selective amplification of microsatellite polymorphic loci (SAMPL), microsatellites amplified fragment length polymorphism (M-AFLP)43, and methylation-sensitive amplified polymorphism (MSAP)44. Although some of these methods seemed to be effective at identifying intra-varietal polymorphisms, they were generally laborious, expensive, time consuming, and difficult to employ in laboratories with low specialisation. Therefore, we focussed our analyses on the identification of SNV markers and on the development of an effective SNV genotyping system that is fast and easily exportable to all laboratories. Starting from the 28,870 SNVs specific to one of the three sequenced ‘Nebbiolo’ clones, we selected SNVs located in genomic regions where TaqMan® genotyping assays were applicable. The Sanger sequencing showed a rate of confirmation of 90% for SNVs common to three clones, while for putative clone-specific SNVs the percentage was around 61%. The majority of the non-confirmed SNVs were predicted to be heterozygous in one clone, but after Sanger sequencing, they resulted homozygous concordant with the other two clones , in comparison to a total of 28,870 Nebbiolo clone-specific SNVs, can be partially linked to the closer genetic relationship either among the three ‘Pinot noir’ clones and between the clones and the reference genome PN40024, and also likely derived by the low sequencing coverage. Indeed, the sum of the sequences shared by one of the three ‘Pinot’ clones and reference genome represents only 4.5 Mb (around 1% of grape genome) at 6-fold genome coverage9. A total of 14 SNVs instead were identified between white wine Spanish cultivar ‘Pedro Ximenes’ and the ‘Corinto bianco’, its parthenocarpic seedless somatic variant, starting from RNA-seq data of flower buds45. Despite the low level of polymorphism between these two somatic variants, these SNVs resulted particularly interesting because involving genes potentially responsible for parthenocarpic phenotype45. Results comparable with ‘Nebbiolo’ data have been obtained after the sequencing of four ‘Pinot’ somatic variants and two ‘Sangiovese’ clones46. In ‘Nebbiolo’, by comparing the aligned reads to PN40024, more than 7,200,000 SNVs have been identified in the three clones, while only 4,600,000 in ‘Pinot blanc’ and ‘Pinot Meunier’, and about 6,000,000 in ‘Sangiovese’ clones46. These data suggest that ‘Nebbiolo’ and ‘Sangiovese’ are genetically more distant to PN40024 than the ‘Pinot blanc’ or ‘Pinot Meunier’, and likely the higher average coverage of ‘Nebbiolo’ and ‘Sangiovese’46 genomes could influence positively the number of SNVs identified. In addition, on 55 SNVs detected between ‘Sangiovese’ clones after reads filtering, only three were validated, suggesting a close relationship between the two clones46. On the contrary, our initial choice of three phenotypically divergent ‘Nebbiolo’ clones . In the other clones analysed we did not observe any ‘unconventional’ allelic calls as reported for CVT 185  and/or the introduction of a single genotype. The early quotations of ‘Nebbiolo’ in Valtellina date back to the end of the sixteenth century23, but were reported three centuries earlier in Piedmont. In northern Piedmont (Canavese and High Piedmont) and the lower Aosta Valley, in addition to the likely progenitor genotype D, other genotypes such as F and C were also present; these genotypes showed a central position in the network 52.In conclusion, the sequencing of three ‘Nebbiolo’ clones has provided interesting insights about the genetic peculiarities of this cultivar and its intra-varietal variability, which is useful for clonal identification. The sequencing of multiple clones for a single cultivar is an innovative approach, and for the first time, these analyses have been exploited to develop an efficient and reliable method for clonal identification in grapevine. The knowledge of the genetic basis of multiple variants present in grapevine associated with functional genomics studies will likely be implemented into classical breeding methods and would be fundamental for large-scale applications of the new ‘sustainable biotechnologies’  registered in the Italian National Register of Grape Varieties by the Institute for Sustainable Plant Protection, National Research Council (IPSP-CNR) were selected for whole-genome sequencing . Plants were trained to a vertical trellis using Guyot pruning; conventional agronomic management was regularly applied in the vineyard. Twenty-seven samples were collected from different organs and at different phenological phases according to the E-L system modified by Coombe Genomic DNA (1.5 μg of each clone) was sonicated for 115 s using a Covaris S2 instrument  and purified using Agencourt AMPure XP beads  in two steps (0.45x and 1.3x) in order to obtain fragments ranging from 200 bp to 800 bp in length. The quality of the fragmented DNA was determined using an Agilent DNA 1000 kit (Agilent Technologies) and an Agilent 2100 bioanalyzer. Genomic library preparation was carried out using the TruSeq DNA Sample Prep Kit v2  according to manufacturer’s instructions. Genomic libraries were sequenced using the TruSeq Sequencing by Synthesis Kit v3-HS and the TruSeq Paired-End Cluster Kit v3-cBot-HS (Illumina) using three lanes of an Illumina HiSeq. 1000 sequencer according to the manufacturer’s instructions to generate 100-bp paired-end reads.https://github.com/vsbuffalo/scythe); (iv) 3’ ends of reads were trimmed with a quality threshold of 20 spanning a window of 10 bases using Sickle ver. 0.940 (https://github.com/najoshi/sickle); and (v) Reads shorter than 20 bp were discarded. The heterozygosity rate was estimated for the CVT 71 clone using the GCE tool (https://arxiv.org/abs/1308.2012).The sequencing reads were filtered using the following protocol: (i) Reads having more than 10% of undetermined bases or more than 50 bases with a phred score quality <7 were discarded using a custom script; (ii) For genomic libraries only, polymerase chain reaction (PCR) duplicates were removed with a custom script; (iii) Sequencing adapters were clipped using Scythe software ver. 0.980 56 and of redundant sequences and non-protein-coding assemblies using EvidentialGene ver. 2013.09.13 . The filtered transcripts were incorporated into the PN40024 gene annotation using PASA ver. r2014-04-1757. Assembled transcripts not incorporated into the annotation were queried against the RefSeq ver. 2016–08 protein database using BLAST ver. 2.2.2858 and filtered of putative contaminants using MEGA ver. 459, selecting only sequences assigned to the Viridiplantae clade. Comparison with other transcripts were performed by local alignment using BLAST ver. 36 × 160. Putative novel gene models and selected non-aligning transcripts were functionally annotated by Blast2GO61.An RNA library for annotation purposes was produced that pooled the RNA extracted from 27 samples Table  using th62. Primer pairs were designed using Primer3 web ver. 4.0.0 software (http://primer3.ut.ee/) and reported in Table ® SV gel and PCR Clean-Up System , and DNA was quantified using a NanoDrop 2000 spectrophotometer (Thermo Scientific). Sequencing was performed using the Big-Dye Terminator v1.1 Cycle Sequencing Kit (Applied Biosystems) following the manufacturer’s instructions. PCR products were purified using the DyeEx 2.0 Spin Kit  and analysed using a 3130 Genetic Analyzer capillary sequencer (Applied Biosystems).For transcript validation, the RNA extracted from different ‘Nebbiolo’ clones and cultivars Table  and S6 wV. vinifera PN40024 12x genome assembly as references using BWA ver. 0.6.2-r12663 with the default parameters. SNVs and short INDELs for each clone were detected using the GATK ver. 2.4.7. pipeline64: (i) Reads that aligned uniquely to the genome were selected by setting a mapping quality ≥ 1; (ii) Read duplicates were marked and read groups replaced using Picard tools ver. 1.96 (https://broadinstitute.github.io/picard/); (iii) Local reads were realigned with the GATK ‘IndelRealigner’ to minimise artefacts due to INDELs; and (iv) Variant calling was performed with GATK in ‘UnifiedGenotyper’ mode.Filtered reads were aligned to the 65 on the V1 version of the annotation of the PN40024 genes (http://genomes.cribi.unipd.it/DATA/). Genes associated with SNVs were grouped using Blast2GO54. GO enrichment analysis was applied to gene variants in ‘Nebbiolo’ using the BiNGO 3.0 plug-in tool in Cytoscape ver. 3.2 as described by Maere et al.26. Over-represented PlantGOslim categories were identified using a hypergeometric test with a significance threshold of 0.05.The biological effects of identified variants were predicted using SNPeff ver. 3.066 and the database of V. vinifera V1-R repeats retrieved from the website of the CRIBI Biotechnology Center (http://genomes.cribi.unipd.it/). Spurious alleles were also discarded from the SNV set. To remove non-informative variants, we initially tried to exclude the low-confidence SNVs with the ‘Variant Filtration Tool’ of GATK using quality parameters suggested in ref.46: (i) phred-scaled quality score (QUAL) < 100; (ii) coverage <0.5 times the average coverage; iii) coverage >3 times the average coverage; (iv) strand bias (SB) > 0; (v) Fisher strand (FS) < 1; (vi) distance from the end of the read for reads with the mutated allele (ReadPosRankSumTest) <2 and >2.5; and (vii) minimum allele frequency (AF) < 0.2. The average coverage of filtered sequencing reads was estimated to be approximately 30- fold for each clone using Bedtools ver. 2.17.0; therefore, the maximum allowable coverage was initially set to 90 fold, and the minimum allowed was set to 15 fold. Since we noticed that some of these criteria were too stringent and other too permissive to allow a reliable identification of ‘Nebbiolo’ clones’ SNVs, we decided to use quality parameters of the set of validated SNVs to recalibrate the whole set of called variants. We thus discarded low-confidence SNVs according to the following parameters: (i) coverage <15; (ii) Fisher strand (FS) > 10; (iii) QualbyDepth <10; (iv) ReadPosRankSum >2. Moreover, based on characteristics of validated SNVs, we discarded homozygous alternative (or reference) SNVs which resulted with more than 2 reads mapped on the reference  allele, to avoid retaining false positive variant calls.To filter the identified SNVs, those located in repetitive regions were excluded using both Bedtools® SNV Genotyping Assay probes (Applied Biosystems) within a 300–500-bp range including the polymorphism using the software Primer Express ver. 3.0 ; (ii) the manual review of the BAM alignment files for the exclusion of any possible artefacts ; and (iii) the alignment of the 300-bp region surrounding the SNV on the V. vinifera reference genome using BLASTN ver. 2.2.28+58, excluding sequences with multiple hits throughout the genome.Candidate SNVs for validation should also fulfil the following criteria: (i) the feasibility of designing TaqManhttp://primer3.ut.ee/). Primers were designed with the following criteria: (i) melting temperature between 52 and 65 °C; (ii) product size of 300–500 bp, (iii) primer length of 18–20 bp, (iv) and GC content between 30 and 70%. PCR amplifications were performed in a volume of 40 µL containing 80 ng of DNA, 1x KAPA Taq Buffer A containing 1.5 mM MgCl2 , 0.2 mM dNTPs, each primer at 0.5 µM and 0.5 U of KAPA Taq DNA polymerase (KAPA Biosystems). The PCR conditions included an initial denaturation step at 95 °C for 3 min followed by 35 cycles of denaturation (95 °C for 30 s), annealing , and extension (72 °C for 1 min). The final elongation step was carried out at 72 °C for 5 min. Amplification products were purified using the Wizard® SV gel and PCR Clean-Up System , and sequenced as above described.SNV validation was performed by the amplification of 300–500-bp genomic regions including the SNVs, followed by Sanger sequencing. Sequences flanking the SNV mutation were selected from the reference genome PN20024 and used to design primer pairs using Primer3 web ver. 4.0.0 software (® SNV genotyping assay (Applied Biosystems). Among these samples, 40 accessions were clones officially registered in the Italian National Register of Grape Varieties and were sampled from the primary source plants. Fifty-eight accessions were sampled from vineyards in the Piedmont, Lombardy, and Aosta Valley regions. DNA was extracted from young leaves using a plant/fungi DNA isolation kit . Chimerisms were investigated by extracting DNA from berry skin (L1 + L2) and berry flesh (L2) of the three sequenced clones. To avoid contamination, berry flesh was isolated by dissecting the cells between the berry skin and the tissue surrounding seeds as previously reported19. All samples were initially genotyped at six SSR markers27 in order to confirm the varietal identity of the samples. PCR amplifications and SSR analysis were performed according to the procedures described by Ruffa et al.67.A total of 98 ‘Nebbiolo’ samples were analysed at 10 SNV marker locations Table  using a SNVs were analysed by qRT-PCR using specific TaqMan probes designed with Primer Express ver. 3.0  Table . The amp68. Genetic distances  were computed as D = [1 − ] using Microsat software69. A median network was also constructed using the program Network ver. 4.570.The genetic relationships among the different genotypes were investigated using two types of analysis. A UPGMA was used to construct and draw a dendrogram from the genetic similarity matrix using MEGA ver. 5.05http://ddlab.sci.univr.it/files/Nebbiolo/Nebbiolo.clones.filtered.SNVs.vcf. Nebbiolo CVT71 specific transcripts sequences (Table http://ddlab.sci.univr.it/files/Nebbiolo/Nebbiolo_CVT71_specific_transcripts.fasta and http://ddlab.sci.univr.it/files/Nebbiolo/Nebbiolo_CVT71_annotation.gff3.Raw sequenced reads can be found in the NCBI Sequence Read Archive under accession numbers SRR5626055, SRR5626056, SRR5626393 and SRR5626750. Variation data are downloadable as VCF files from es Table  togetherSupplementary informationTable S5Table S7Table S8Table S9Table S10Table S11Table S12Table S13


The ‘thermal grill illusion’ (TGI) is a unique cutaneous sensation of unpleasantness, induced through the application of interlacing warm and cool stimuli. While previous studies have investigated optimal parameters and subject characteristics to evoke the illusion, our aim was to examine the modulating effect as a conditioning stimulus. A total of 28 healthy control individuals underwent three testing sessions on separate days. Briefly, 15 contact heat stimuli were delivered to the right hand dorsum, while the left palmar side of the hand was being conditioned with either neutral (32 °C), cool (20 °C), warm (40 °C), or TGI (20/40 °C). Rating of perception  and evoked potentials  to noxious contact heat stimuli were assessed. While cool and warm conditioning decreased cortical responses to noxious heat, TGI conditioning increased evoked potential amplitude (N1 and N2P2). In line with other modalities of unpleasant conditioning , cortical and possibly sub-cortical modulation may underlie the facilitation of contact heat evoked potentials. In 1896, Torsten Thunberg first described the paradoxical sensation of heat in response to interlaced warm and cool stimulation. Since these seminal observations, the “thermal grill illusion” (TGI) has been described extensively using various modern stimulating devices. Of defining characteristics, the TGI is reported as a uniquely “unpleasant” somatosensory experience123456769121314somatosensory input, which is typically perceived as both painful and unpleasant161718special senses)121420212223Investigating the conditioning effects of afferent stimuli on responses to noxious input has generated a wealth of knowledge regarding endogenous pathways modulating pain. The notion of “anti-nociception” has been largely explored using conditioning The objective of the current study was to address the heterotopic conditioning effect of an unpleasant somatosensory afferent stimulus  on responses to noxious contact heat stimulation. In line with other forms of unpleasant sensory conditioning, we hypothesized that the TGI would result in increased responses to noxious afferent stimulation. To explore changes in cortical activity, the conditioning effect of the TGI was examined using contact heat evoked potentials (CHEPs).A total of 32 healthy control individuals  were recruited. Inclusion criteria were (1) age between 18–40 years, (2) being naïve to TGI and CHEPs, and (3) fluent in English or German. Exclusion criteria comprised pregnancy, intake of any medication (except birth control), and previous participation in a TGI or CHEPs study. All participants provided written informed consent and all procedures described below were in accordance with the Declaration of Helsinki and approved by the local ethics board ‘Kantonale Ethikkommission Zürich, KEK’ .Prior to the commencement of the study, all individuals were interviewed to measure pain catastrophizing using the German or English version of the pain catastrophizing scale (PCS)2627283031The study consisted of three different testing days differing only by the conditioning stimulation applied . On the During the experiment, subjects were lying in a supine position with eyes open. The experiment consisted of three measurement blocks of combined conditioning and contact heat stimulation separated by 5-minute rest breaks. The first two blocks of contact heat stimulation were delivered to the right hand during neutral (32 °C) conditioning. In a previous study, we observed significant reductions in CHEPs following repetitive stimulation in the same cutaneous areaResponses to noxious stimuli were examined using a contact heat stimulator . The thermode surface (diameter: 27 mm) consists of a heating thermo-foil covered with a layer of thermos-conductive plastic. The nominal heating rate of this device is 70 °C/s (thermo-foil), with a cooling rate of 40 °C/s (peltier element). From peak temperature, the thermode immediately returned to baseline. All measurements of contact heat stimulation were made from a baseline temperature of 42 °C to a peak temperature of 52 °CCHEPs were recorded with 9 mm Ag/AgCl surface disc electrodes filled with conductive adhesive gel. Scalp recording sites were prepared with Nuprep  and alcohol. In brief, CHEPs are an electrophysiological approach to explore cortical responses to A-delta afferents activated by rapid heat stimuli delivered peripherally. The early CHEPs component (N1) represents a direct measure of nociceptive input at the primary somatosensory cortex38384142434445http://www.sms.hest.ethz.ch/; Engineering Department). The device is equipped with 10 bars  each consisting of three Peltier elements, all of which capable of dynamic cooling and heating within a minimum range between 18 and 42 °C. All thermoelectric bars were individually controlled by LabVIEW (LV) software . The software was developed at the Spinal Cord Injury Center .A customized thermal grill device was built by Sensory-motor system laboratory at the Swiss Federal Institute of Technology (ETH) Zurich  from the neutral condition to warm, cool, and interlaced cool/warm conditioning. “Neutral” CHEPs outcomes were examined to determine their distribution . Based on an evaluation of skewness and kurtosis parametric statistics were planned. An unstructured linear mixed effects model was applied to examine the main effect of repeated stimulation  and interaction effect with different condition modalities . The advantage of the LMM is that one can account for missing data when analyzing longitudinal dataWe next considered the relationship between rating of unpleasantness and changes in CHEP outcomes during TGI conditioning. Changes in N1/N2P2 amplitude and pain rating  were examined using separate analysis of variance (ANOVA) for N1 and N2P2. The effect of unpleasantness was first examined by way of dichotomizing subjects as “responders” and “non-responders”. TGI responders were defined as any subject that reported the TGI as more unpleasant than warm and cool conditions. Non-responders perceived the TGI as equally or less unpleasant than warm or cool conditioning. Responders/Non-responders was treated as a between subject factor in the models. In order to further explore the relationship between perception and changes in CHEPs outcomes, a second ANOVA explored the effect of TGI unpleasantness as a covariate.All statistical testing was performed in SPSS (V. 23) and statistical significance was set at p < 0.05.Out of 32 healthy subjects enrolled in the study 4 had to be excluded due to: 1) technical problems during data acquisition (n = 2) and 2) intolerance of the contact heat stimuli applied (n = 2). The remaining 28 subjects comprised of 11 men and 17 women (mean age: 29.4 ± 6.3 years). The mean score of the PCS questionnaire was 11.9 ± 7.7. Participants’ characteristics are summarized in unpleasantness = 3.2 ± 2.8) and painful by one individual (NRSpain = 2 ± 0). In response to warm conditioning, four individuals reported unpleasantness (NRSunpleasantness = 1 ± 0) and one pain (NRSpain = 1). The descriptors used for cool stimulation were cool (n = 18), cold (n = 9), and freezing (n = 1). The warm modality was described as warm (27) and burning (1). A total of 13 individuals indicated the interlaced application of cool/warm to be unpleasant (NRSunpleasantness = 3.7 ± 2.1) , no unpleasantness or pain was reported. The cool modality was reported to be unpleasant by five individuals  are presented in increased during interlaced warm and cool conditioning  , which depended on the conditioning modality . Significant decreases were observed between during warm  and cool conditioning . In contrast, N2P2 amplitude was significantly = 0.005) .increased N1 amplitude  . The modulation of N1 amplitude was, however, dependent on the conditioning modality . During cool conditioning, N1 amplitude significantly decreased . While warm conditioning had no significant effect , TGI conditioning significantly = 0.021) . There w“Responders” and “non-responders” yielded similar changes in N1  and N2P2 amplitudes . As a covariate, there was no effect of “unpleasantness” rating on N1  or N2P2 amplitude .In the 100-year history of the TGI, research has focused primarily on establishing the quality of sensation unmasked by stimulating with interlaced, innocuous warm and cool stimuli35674950Several lines of converging evidence indicate an important distinction between early and late CHEP waveforms, whereby N1 represents a direct measure of nociceptive input and activation in the primary somatosensory cortex, and N2 and P2 represents later stage processing in the ACC and secondary somatosensory cortex38525356Based on increases in both N1 and N2P2 amplitude during TGI conditioning, it is intriguing to consider that responses to noxious heat were modulated sub-cortically. One potential explanation is that modulation occurs at the spinal level. Previous investigations have demonstrated increases in nociception during unpleasant auditory22121523241224596162Interestingly, however, TGI related unpleasantness did not have a significant effect on the magnitude of changes in CHEPs – that is, TGI responders demonstrate increases comparable to non-responders. In our study, 10/28 healthy subjects described the TGI as more unpleasant than warm and cool conditioning (responders = 36%). This number is somewhat lower than previous studiesThe lack of a relationship between unpleasantness and the facilitation of CHEPs may be a function of underpowered statistics . More generally, problems may arise from defining “responders”. In the current study, a responder had to identify the TGI as more unpleasant than either warm or cool conditions. Some subjects did not report TGI as “unpleasant” but still physically removed their hand during presentation with interlaced warm and cool bars. This reflexive motor response could be construed, at some level, as evidence of discomfort or unpleasantness associated with the thermal grill. Alternatively, withdrawal  may reflect the TGI as a “metaesthesic” sensationThe current study was designed with all subjects undergoing the TGI on the second day of testing. Subjects were randomly assigned to cool or warm for the first session, and crossed into the other condition at the third session. This design was intended to overcome the problem that varying the time from the original familiarization period could influence future responses to the TGI. One potential problem with this approach is that the conditioning effect of TGI on CHEPs may depend on whether the warm or the cool condition came first. We also cannot rule out that the “TGI-effect” on CHEPs was related to being tested on day 2.Another limitation is that we did not specifically assay changes in arousal. Previous studies demonstrate a strong attention/vigilance component for N2P2, and, to a lesser extent, N1396667In summary, this is the first study providing evidence that heterotopic TGI conditioning facilitates nociceptive evoked potentials. Based on the pattern of facilitation , the TGI modulated CHEPs sub-cortically . Facilitation occurred independently of reported unpleasantness, suggesting that the TGI has a similar pro-nociceptive effect regardless of how it is perceived. Future studies are warranted to further examine the somatosensory conditioning effects of the TGI on cortical responses to afferent stimulation.How to cite this article: Jutzeler, C. R. et al. Thermal grill conditioning: Effect on contact heat evoked potentials. Sci. Rep.7, 40007; doi: 10.1038/srep40007 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


We compare the in vitro growth dynamics of the adapted virus with those of the original strain as well as all possible reassortants using reverse genetics. This full factorial design showed that viral gene segments are involved in complex epistatic interactions on virus fitness, including negative and sign epistasis. We also identify two point mutations at positions 67 and 113 of the HA2 subunit of the hemagglutinin protein conferring a fast growth phenotype on the naïve avian virus in swine cells. These HA2 mutations enhance the pH dependent, HA-mediated membrane fusion. A global H1 maximum-likelihood phylogenetic analysis, combined with comprehensive ancestry reconstruction and tests for directional selection, confirmed the field relevance of the mutation at position 113 of HA2. Most notably, this mutation was associated with the establishment of the H1 ‘avian-like’ swine influenza lineage, regarded as the most likely to cause the next influenza pandemic in humans. This multidisciplinary approach to study the genetics of viral adaptation provides unique insights on the underlying processes leading to influenza emergence in a new host species, and identifies specific targets for future surveillance and functional studies.The emergence of pathogenic RNA viruses into new hosts can have dramatic consequences for both livestock and public health. Here we characterize the viral genetic changes that were observed in a previous study which experimentally adapted a field isolate of duck influenza virus to swine respiratory cells. Both pre-existing and  Influenza A viruses pose grave health threats to humans and animals worldwide. Most influenza A subtypes have been found in wild aquatic birds, which as such provide a global reservoir for these viruses in nature . InfluenInfluenza virus is a primary respiratory pathogen of swine, that has direct consequences on pig health, welfare and production . InfluenMany strains of avian influenza virus have the capacity to infect swine or swine cells, but most of them do not seem fully adapted to readily spread in swine populations and rather need to evolve further. For instance, in an experimental infection of pigs, titres of an H1N1 avian virus recovered from nasal swabs were lower than those of a swine influenza virus of the same subtype . Similarst century, particularly in the USA but has since dwindled , sodium pyruvate (1 mM) and foetal calf serum . Infections were carried out replacing FCS with 0.3% (w/v) bovine serum albumin (BSA) and adding 0.25 µg/ml trypsin (Worthington). Cells were cultured at 37 ºC in a 5% CO2 atmosphere.The A/mallard/Netherlands/10-Nmkt/1999 (H1N1) duck influenza isolate  was passaged 10 consecutive times in Newborn Pig Trachea (NPTr) swine respiratory cells , obtaineVirus rescues were carried out to retrieve the parental and adapted virus consensus as well as all 14 different reassortants, allowing us to perform growth rates assessment for all these variants. Virus rescue was conducted using the fusion-enhanced method described in (i) Laboratory protocols. In order to study viral growth efficiency in culture, assay conditions were optimised to enable study of the viral growth rate during the exponential growth phase. Replicate infections were carried out in six-well plates seeded with 7.5 × 105 cells per well and infected on the next day with 0.1 viral genome copies per cell. Cells were seeded in FCS-supplemented media and infected in FCS-free, trypsin-supplemented media. On the day of infection, the FCS-supplemented medium was removed, cells were washed with PBS and infected with 500 µl of infection medium containing 7.5 × 104 viral genome copies per well. The inoculum was left onto the monolayer of cells for 1 h at 37 °C and 5% CO2 for the virus to adsorb. After 1 h, the inoculum was removed and the monolayer was rinsed with PBS to remove unadsorbed virus. The culture was then covered with 2 ml of fresh medium. Samples consisting of culture supernatant were taken at 1, 18, 24, and 30-h post-infection, time being counted from the moment the inoculum was put onto the cells. Samples were snap frozen at −70 °C and then processed for quantitation of viral yields. In each assay, uninfected wells were included as controls and handled in the same way as the tests wells; no evidence of viral growth was detected in these.3 to 3 × 103 copies-to-one-pfu for both viruses). A formal validation of the use of genome copy numbers to estimate exponential growth rate is provided in the Genome copy numbers in the supernatants were estimated by real-time, quantitative PCR (qPCR). This approach was chosen because it allows an estimation of viral genome copy numbers that is independent from the infectivity of the virus in any given system, arguably making it the most objective quantitation of virus yield. Adaptation to different cell types may impact on apparent yield when assayed by cell culture methods, i.e. may affect the ‘efficiency of plating’, while the alternative of using HA titre is insufficiently sensitive to monitor virus yields below a certain threshold. The ratio of genome copies to plaque forming units (pfu) was very similar between the two rescued viruses rWt and rAd (2 × 10R2) was over 0.99.The QiaAmp viral mini kit (Qiagen) was used for RNA extraction from allantoic fluids and cell culture supernatants (liquid samples) according to manufacturer’s instructions. Reverse transcription of viral RNA into complementary DNA (cDNA) was performed using Fermentas RevertAid Premium reverse transcriptase as per manufacturer’s instructions, using a primer specific for the 3' conserved region of the influenza A segment 7 viral RNA (vRNA) . Quantitative PCR (qPCR) was performed using Qiagen QuantiTect Probe PCR kit in 20 µl reactions containing 10 µl 2× PCR master mix, 0.4 µM of each primer , 0.2 µM of a dual-labelled probe (SePRO: 6FAM-TCAGGCCCCCTCAAAGCCGA-BHQ1a), 2 µl of template cDNA, and RNAse-free water to 20 µl. These primers and probe [named after ] were mo(ii) Mathematical modelling. Viral yields from growth assays were log-transformed, and negative samples (i.e. no genome copy detected) were assigned a value of zero. The experimental protocol above was optimised so that growth curves between 1 h and 30 h post infection could be modelled by a straight line  chicken red blood cell (RBC) solution and 64 hemagglutination units of virus in 50 µl. Chicken RBC were purchased from TCS Biosciences (#FB010AP). The A/PR/8/34 backbone was used to segregate HA-mediated effects from those of the neuraminidase (which was highly active for the rescued avian viruses and interfered with the performance of the fusion assay by causing intense virus elution). After a 30-min hemagglutination time, 150 μl of citric acid buffer at varying pH (4.0–6.0 range) was added to each well and the plate was incubated for 30 min at 37 °C. The plate was centrifuged at 2000 rpm for 8 min at 4 °C and 150 μl of supernatants from each well were transferred into a 96-well, flat-bottomed plate. Hemoglobin release was quantified by measuring absorption at 450 nm using a Biorad iMarc Microplate Reader. A negative control was included at each pH with no virus added. A 100% lysis control was obtained using 0.2% Triton X-100 .Influenza A H1 hemagglutinin nucleotide sequences were downloaded from the NCBI Influenza resource . Queriesn = 846 sequences, 458 from aquatic birds and 388 from swine). We reconstructed changes at position 67 and 113 in HA2 (see Results) by parsimony. We confirmed that the S113F transition occurred coincident with the jump to swine using BEAST v.1.8.2 (n = 357 unique amino acid sequences), and tested for further diversification following the host jump using FADE, an approximate but fast approach to screening amino acid sites (and variants at those sites) for directional selection, as implemented in Datamonkey (http://tree.bio.ed.ac.uk/software/figtree/). Assignment of swine H1 hemagglutinins to their respective clade  was based on a number of published studies  in NPTr cells.The parental virus stock is hereafter referred to as ‘Wt’ (for ‘wild type’) and the swine cell-passaged stock as ‘Ad’ (for ‘adapted’), and in-depth genome analyses of both viral stocks have been described in detail previously .10 difference in yield over rWt every 10 h (P < 0.001). A similar growth rate assessment in duck embryo fibroblasts (DEF) showed no difference between the two viruses in duck cells (P = 0.943), suggesting that the effect on growth rate was cell-type dependent.ck cells P = 0.943P = 0.726). The two-way epistatic interactions tended to be more negative than the three-way interactions . The two-way epistasis between the three pairs of segments with positive main effects was even more negative  although none of these average values were statistically different from zero. However, the epistatic interaction between the two most beneficial segments (2 and 4) was strongly and very significantly negative . In fact, we found some evidence for sign and double sign epistasis as the 2 + 4 double mutant had lower fitness than both the virus carrying only the mutated segment 2 (P = 0.024) and the virus carrying only the mutated segment 4 (P = 0.054) (P < 0.001), and the 2 + 7 ‘double mutant’ had lower fitness than both the virus carrying only the mutated segment 2 (P < 0.001) and the virus carrying only the mutated segment 7 (P = 0.002).The rWt and rAd viruses differed by a total of 25 amino acids distributed on six described viral proteins as follows (number of differing amino acids between square brackets): PB1 [7], PB1-F2 [11], HA [2], M42 [2], NS1 [2], NS2 [1]. An additional point mutation on segment 3 also became dominant during the experimental adaptation process, but was not studied further here as it did not modify any known influenza protein. As the selected proteins are encoded by gene segments 2, 4, 7, and 8, we sought to investigate the respective contribution of these four gene segments using reverse genetics in the common backbone of segments 1, 3, 5, and 6 . Our ful= 0.054) . Similarde novo during the adaptation experiment. It was thus anticipated that these two segment 4 changes could each be very consequential, and in the following we focus on these two mutations to explore in more details their effect on viral growth.The significant main effects of segments 2 and 4 indicated that the specific mutations carried by these segments were involved in adaptation to swine respiratory cells. Segment 2 of the adapted virus carried 18 coding and 96 non-coding mutations while segment 4 carried only 2 mutations, both of them coding. Moreover, all of the nucleotide differences observed in segment 2 originated simultaneously during the adaptation due to the selection of a reassortant from a low-level subpopulation in the initial virus inoculum . Thus, aIn order to determine the individual contribution of each these two hemagglutinin changes, we rescued the two chimeric constructs each bearing a single mutation in an otherwise rWt backbone. The two mutations in question are G67S and S113F on the HA2 subunit, numbering from the N-terminus of the fusion peptide . The Wt and Ad hemagglutinin alleles are designated ‘WW’ and ‘AA’ respectively and the two single mutants are ‘WA’ and ‘AW’. The HA2 G67S mutation is located in the middle of a 22-aminoacid region that undergoes a conformational change from a loop to an α-helix at acidic pH, contributing to fusion of the viral and endosomal envelopes . The HA2To test the effects of the mutations on the membrane fusion process, the four possible combinations of alleles were tested in a quantitative hemolysis assay where excess virus bound to RBC membranes results in release of hemoglobin upon low pH exposure. Red blood cell lysis was dependent upon the presence of virus in the pH 4.8-6 range, each of the 4 viruses showing a distinct pH profile with a characteristic threshold pH and optimum pH for lysis . The Wt in vitro of the two hemagglutinin mutations identified in this study for viral fitness in swine tracheal cells , and mapped the HA2 mutations identified in this report onto the phylogeny. The phylogeny showed three major swine influenza clades , while a few waterfowl isolates had a serine at position 67 (crosses). We also used the FADE method to test whether there was statistical evidence for ongoing diversification at the amino acid level as might be anticipated for adaptational “fine-tuning” observed for previous cross-species transitions  showed rarer, sporadic occurrences of 113F or 67S .The objective of this research was to study the effects of mutations involved in the adaptation of an H1 avian influenza virus to a swine host. Experimental adaptation to swine cells started from a polymorphic uncloned, low egg-passage avian field-isolate population consisting of a mixture of viruses  represende novo spontaneous mutations. Reverse genetic studies of all reassortants allowed us to explore the individual effects of the preferentially selected segments of the adapted virus as well as the interaction between these segments. Two segments (2 and 4) stood out in this analysis as being associated with important main effects on virus growth. In particular a clear overall growth advantage was mapped to two novel mutations on segment 4 encoding the hemagglutinin. In addition, our full-factorial design demonstrates the existence of significant epistatic interactions among segments. These epistatic interactions, including sign epistasis, suggest that the fitness landscape may be characterized by several fitness peaks that may be attained by different combinations of segments. Interestingly, the two-way epistatic interactions between adaptive mutations tended to be negative. This conforms to expectations in a single peak fitness landscape where the convex shape of the peak implies that the fitness gain associated with each beneficial mutation decreases when the phenotype is closer to the optimum  with a large, hydrophobic residue such as phenylalanine or leucine at HA2 position 113 may be an important step in the direct adaptation of fully avian influenza viruses to swine. At HA2 position 67, the species association pattern was less clear, with the mutated amino acid (serine) being infrequent in all clades. This further implies the existence of strong epistatic interactions in this virus, as there may be other mutations that can substitute for 67S in helping potentiate the role of 113F(L) in the successful establishment of a swine influenza lineage from aquatic bird precursors.Hemagglutinin-mediated, pH-dependent membrane fusion is an essential process in the viral replication cycle. Following endocytosis by the cell, acidification of the endosome triggers an irreversible change in HA conformation that causes the viral envelope to fuse with the endosome membrane. This allows the viral genetic material to enter the cytoplasm, paving the way for all subsequent steps of the replicative cycle. Here, pH dependent lysis patterns showed that the two HA mutations had distinct phenotypic effects on the fusion process. Fusion of the ‘WA’ single mutant is likely to occur at a higher pH whereas for the ‘AW’ single mutant the process occurs more efficiently. The two mutations operate cooperatively, to induce greater fusion at higher pH threshold, and these effects were well correlated with the growth speed phenotypes brought about by the two hemagglutinin mutations alone and in combination in swine cells . The incA higher fusion pH threshold would result in reduced infectivity after exposure to an acidic environment (i.e. reduced acid stability)  and the in vivo virulence in mammals is ∼5.2–5.4. Conversely, greater acid stability has been demonstrated for a number of duck compared to human viruses (Other studies on this topic have been conducted in laboratory animal models , that ar viruses , althoug viruses  and we a viruses . Of note viruses .in vivo. Yet the phylogenetic analysis carried out in this study clearly demonstrates the relevance of these mutations in the field. Influenza virus surveillance in swine should thus consider S113F/L as a signature mutation indicative of a potential incipient emergence event.This study of the genetics of adaptation of H1 influenza to swine respiratory cells identifies mutations that may be involved in faster growth in this novel environment. Epistatic interactions on fitness suggest that the fitness landscape of influenza is complex and several combinations of mutations may lead to successful transmission to swine. Nonetheless the mutation at HA2 position 113 stands out in this analysis. Future studies should be carried out to help characterize other consequences of this mutation Supplementary DataClick here for additional data file.


We report a plasmonically enhanced virus inactivation, with greater than 3.7-log reduction measured by virus infectivity assays. Reliable virus inactivation was obtained for 10 s laser exposure with incident laser powers ≥0.3 W. Importantly, the fs-pulse induced inactivation was selective to the virus and did not induce any measurable damage to co-incubated antibodies. The loss in viral infection was associated with reduced viral fusion, linking the loss in infectivity with a perturbation of the viral envelope. Based on the observations that physical contact between nanorods and virus particles was not required for viral inactivation and that reactive oxygen species (ROS) did not participate in the detected viral inactivation, a model of virus inactivation based on plasmon enhanced shockwave generation is proposed.Femtosecond (fs) pulsed laser irradiation techniques have attracted interest as a photonic approach for the selective inactivation of virus contaminations in biological samples. Conventional pulsed laser approaches require, however, relatively long irradiation times to achieve a significant inactivation of virus. In this study, we investigate the enhancement of the photonic inactivation of Murine Leukemia Virus (MLV)  In particular, virus inactivation through exposure to ultrashort laser pulses is emerging as a potential alternative to existing biocides and ionizing radiation techniques7. The current interest in photonic virus inactivation derives from the need for new technologies that achieve a selective inactivation of the pathogens in the presence of other biomolecules or even living cells in food, feed stock in pharmaceutical bioreactors, therapeutic compounds and other sensitive areas with relevance for human and animal health. For many of these applications, harsh chemical or ionizing radiation techniques are not appropriate as they lack sufficient selectivity. Importantly, Kong-Hon Tsen and coworkers have demonstrated in a series of elegant studies that irradiation with femtosecond (fs) laser pulses with visible (425 nm)8 or near-Infrared  wavelengths results in an inactivation of both enveloped and non-enveloped viruses under conditions that do not impact mammalian cells13. Tsen and coworkers postulated that fs laser induced virus inactivation is a non-thermal effect that results from impulsive stimulated Raman scattering (ISRS) driven breaking of non-covalent bonds in the virus10. Although individual broken contacts can reform, the authors argued that an excessive bond-breaking results in an irreversible loss of structural integrity of virus particles6 and potentially in viral protein aggregation5. Theoretical analysis revealed that for ISRS to be effective, high laser intensities are required14. Under these conditions alternative mechanisms to drive structural and chemical transformations exist, including multiphoton absorption. It also deserves mentioning that a different group was unable to reproduce the inactivation of phages through fs laser irradiation15, highlighting the need for further research into the mechanism of inactivation.Pulsed lasers provide new opportunities for imaging or modulating cellular behavior in a diverse range of diagnostic10. The need for long irradiation times limits the scalability of the photonic virus inactivation process and impedes the practical implementation of photonic virus inactivation strategies in many cases.To date, photonic inactivation was successfully achieved with focused fs laser beams and relatively long irradiation times of ≥1 h16, they generate high local E-field enhancements in electromagnetic hot-spots17. The strong E-field generated by the plasmonic nanoparticles can enhance the previously discussed virus inactivation mechanisms and, as we show in this manuscript, facilitate new virus inactivation processes. We demonstrate that resonant nanoparticles whose LSPR overlap with the excitation pulse, enhance the virus inactivation but that non-resonant nanoparticles have no effect. The effect of resonant plasmonic nanoparticles on virus inactivation as function of laser power when irradiated for a short exposure time of 10 s is characterized in detail. Since both efficiency and selectivity are important figures of merit for photonic virus inactivation, we monitored the selectivity towards virus particles by measuring the functionality of IgG antibodies co-incubated with the virus particles during laser exposure. Our data indicate that the plasmonically enhanced photonic inactivation is highly selective towards virus particles and generates no detectable collateral damage to the antibodies, and that the mechanism of inactivation differs from those of previously established photocatalytic18 and photothermal19 inactivation methods.In this manuscript, we explore the plasmonic enhancement of photonic virus inactivation as a possible strategy to overcome some of the challenges associated with pulsed laser driven virus inactivation. Since noble metal nanoparticles convert incident electromagnetic waves into localized charge density oscillations, so called localized surface plasmon resonances (LSPRs)2 and the typical exposure time of the sample to the laser irradiation was 10 sec. All laser irradiation studies were carried out at 22 °C. After irradiation, the samples were immediately stored at 4 °C.The ultrashort pulsed (USP) excitation source used in this study is a femtosecond laser based upon a Legend Elite Duo (Coherent Inc.) Ti-sapphire regenerative amplifier. The laser produces a continuous train of 35 fs pulses at a repetition rate of 1 kHz centered at 805 nm with energies up to 7.5 mJ and spectral width of about 25 nm. The laser beam was incident on a quartz cuvette containing 250 µL of virus sample. Different laser powers on the sample were obtained using beam splitters and directing only a portion of the total laser beam to the sample area. The USP laser spot size was approximately 1 cm22. The nanorod sample was placed in a 1 mm quartz cuvette, which was located in a custom cell filled with water for ultrasound coupling. The cuvette was oriented at an angle of 45° relative to the 0.3 W fs laser beam. The photoacoustic signal (ultrasonic wave) was collected using a 2.25 MHz focused water immersion transducer.The acoustic signal generated by laser irradiated nanorods was collected in a homebuilt ultrasound detector. Figure et al. to synthesize gold nanorods23. 460 μL of a freshly prepared solution of 0.01 M sodium borohydride dissolved in 0.01 M sodium hydroxide was rapidly injected into 10 mL of 0.5 mM HAuCl4 solution containing 0.1 M CTAB under extensive stirring. A change of color from greenish to light brown indicated the successful formation of gold nanoparticle seeds. To synthesize gold nanorods with a longitudinal resonance at ~800 nm, 11.5 μL of 0.1 M silver nitrate solution was added to 10 mL of 0.5 mM HAuCl4 solution containing 0.1 M CTAB. Subsequently, 500 μL of 0.1 M aqueous hydroquinone solution was added, and the resulting mixture was hand-stirred until it became clear. Then, 160 μL of gold seed solution was added under thorough stirring. The resulting mix was allowed to age overnight. To obtain PEGylated nanorods, 2.5 µL of 10 mM PEG2 (HS—CH2CH2—(C2H4O)77—N3) were added together with 2.5 µL of 10 mM HS-(CH2)11-(CH2CH2O)6OCH2-COOH to 1 mL of gold nanorods in the presence of 3% v/v of Tween® 20. The samples were incubated overnight and washed by centrifugation and subsequent resuspension. Alkyne-functionalized annexinV was cross-linked to the azide functionalized nanorods in the presence of 500 μM ascorbic acid and 100 μM CuSO4via CuI catalyzed click-reaction24. The nanorods were cleaned again through repeated centrifugation and resuspension in DDI water or buffer.We used the seed-mediated growth technique described by Vigderman 25. For the virus fusion assay described below, HEK293T cells were co-transfected with pLNC-luc, pCL-Eco and S15-BlaM plasmids. To generate the S15-BlaM expression plasmid that expresses a Src-eptiope tagged β-lactamase fusion protein upon transfection, the N-terminal 15 amino acid sequence of c-Src (S15) was cloned in frame upstream of β-lactamase orf in pcDNA3.1/zeo + (Invitrogen) eukaryotic expression plasmid. S15-BlaM is incorporated into MLV particles upon virus particle budding from the plasma membrane of virus-producing cells27. Virus-containing supernatants were harvested 2 days post transfection, and passed through 0.45 µm filters. Virus was concentrated by ultracentrifugation on a 20% sucrose cushion . Virus pellets were resuspended in PBS, aliquoted, and stored at −80 °C until further use.HEK293T and Rat-2 cells were maintained in DMEM supplemented with heat-inactivated 10% fetal bovine serum (Invitrogen) and Pen/Strep (HyClone). Luciferase expressing, single cycle of replication competent MLV particles (MLV/luc) were derived via co-transfection of HEK293T cells with pLNC-luc  and pCL-Eco  plasmids, as previously describedgag monoclonal antibody; Clone 183-H12-5C; NIH AIDS Research and Reference Reagent Program, contributed by Dr. Bruce Chesebro) in RPMI medium was added to the mixture and the mixture was diluted by adding 1x Tris (pH 7) or PBS (pH 7.4) buffer to final volume of 1 ml. The nanorod to virus ratio was more than 10000:1. The concentration of the nanorods was quantified using a UV-vis spectrometer (Cary 5000 spectrophotometer).PEGylated nanorods or nanorods loaded with annexinV were centrifuged at 5000 rpm for 10 min. The supernatant was discarded and 17 µL of the pellet was added to 50 µL of MLV/luc, followed by overnight incubation at 4 °C. Then, 500 µL of IgG antibody (anti-p243) and Manitol were dissolved in 20 mM Tris (pH 7.0). Then Manganese (III) Tetrakis (4-benzoic acid) Porphyrin (MnTBAP) dissolved in 0.1 M NaOH was added. This solution was subsequently added to virus samples containing antibodies from a hybridoma preparation or to mixtures containing virus, PEGylated nanorods, and antibodies. All samples were diluted with Tris buffer. The final scavenger concentrations were 10 mM Manitol, 10 mM Sodium azide and 0.02 mM MnTBAP. The pH of the final solution was 7.A solution containing three different ROS scavengers were used. Sodium azide  was bound to HIV-Ig  coated wells and detected with unexposed control or laser exposed anti-p24gag monoclonal antibody, and HRP-conjugated goat anti-mouse secondary antibody (Sigma). ELISA was developed with a peroxidase substrate  and the standard curves were generated with each of the control (untreated) or fs laser-exposed anti-p24gag monoclonal antibodies.To test the efficacy of the fs laser inactivation protocol on functionality (epitope recognition) of a monoclonal antibody, an anti-p2429 was utilized with some modification. Briefly, untreated or laser-exposed MLV/luc particles containing S15-BlaM fusion protein was used to infect target cells. After incubating 2 hours at 37 °C, cells were washed with CO2-independent media (Invitrogen) and incubated in CCF2 (fluorogenic substrate of β-lactamase)-containing media at 18 °C over night, washed, fixed with 4% PFA. The number of β-lactamase positive cells was determined by FACS analysis using a LSRII flow cytometer (BD).To investigate MLV/luc fusion to Rat2 target cells, a FACS based assayprior to lysis. The lysates were then used for measurement of luciferase activity using a chemiluminescent reporter . The ratio of the intensity of the luminescence to a calibration standard is measured in RLU (relative light units), and is a linear function of the reporter concentration. If RLUc and RLUs are the measured RLU values of the control and sample respectively, the Log-Reduction Value (LRV) defined as LRV = log10(RLUc/RLUs) gives a quantitative measure of the extent of virus infection in the culture.Virus inactivation was determined by infecting cells (mouse fibroblast cell line) with treated (laser-inactivated) or untreated viruses. Cells were then incubated for 48 h In order to test for potential cytotoxicity of nanorods, laser irradiated and non-irradiated nanorods media were harvested and incubated with Rat-2 cells at 37 °C overnight. The Trypan blue exclusion test was then used to determine the percentage of viable cells.Nanorod samples were run on 2% agarose gels made from 0.5x TBE. The same buffer was used as running buffer. The samples were loaded with ficol and were run with a current of 200 mA, voltage of 140 V for 30 min.The variability in the data were analyzed by Anova with subsequent post-hoc test as implemented in Matlab. Differences between samples with a significance level of P < 0.05 are marked with one asterisk (*), and for P < 0.01 with two asterisks (**). NS was used to mark non-significant differences.The datasets generated during and/or analyzed in the current study are available from the corresponding authors upon request.31. All experiments were performed with a recombinant virus that expresses the luciferase reporter gene upon establishment of productive infection in target cells, providing a robust strategy for the quantification of virus infectivity. In a first set of experiments we tested the hypothesis that nanorods whose LSPR overlaps with the incident fs laser pulse enhances the efficacy of light-induced laser activation. To that end, we compared the viral infectivity obtained with virus particles exposed to fs laser irradiation with constant pulse duration but different average powers. Importantly, we kept the exposure time of the individual samples constant at 10 s, which is 3 orders of magnitude shorter than the exposure time in all previous photonic virus inactivation studies.We chose Murine Leukemia Virus (MLV) as target for our viral inactivation studies due to its similarity with endogenous mouse retroviruses that are known contaminants in the biopharmaceutical industry33. We used gold nanorods with an aspect ratio of around 4, with typical lengths of ~60 nm. We found that these nanorods sustain a longitudinal plasmon mode that peaks close to the wavelength of the fs laser emission (805 nm) as is shown in the UV-Vis spectra of the nanorod “control” (no laser exposure) in Fig. 34 using cetrimethylammonium bromide (CTAB) as ligand, which favors growth along the crystallographic [110] axis. Due to the functionalization of the nanorod surface with CTAB, the nanorods have a positive zeta-potential of approximately ζ =  + 23 mV. As CTAB is cytotoxic, we replaced it with polyethyleneglycol (PEG) ligands. In a first set of experiments we tested the stability of the nanorods when irradiated with 805 nm laser pulses with 35 fs duration for 10 s. We varied the average laser power between 0.3 W, 1.2 W and 3 W and recorded UV-Vis spectra after laser irradiation. These spectra and the spectrum of the non-irradiated control sample are summarized in Fig. 32. The peak wavelength of the longitudinal mode intensities and the associated full width at half maximum (FWHM), are plotted in Fig. The LSPRs of gold nanoparticles are strongly morphology dependent, and the aspect ratio of nanorods represents a rational control parameter to tune the plasmon resonance across the visible range of the electromagnetic spectrum to the Near-Infrared (NIR) and beyond36 of the nanorods leads to shorter and wider rods with increased oscillator strength for the transverse plasmon mode and a blue-shifted longitudinal plasmon resonance. Early studies experimentally showed that an average of ~60 femtojoule (fJ) energy, which is close to our experimental condition, is required to melt a single gold nanorod with an aspect ratio ~437. Fig. 38. The different spectral responses account for the broadening of the plasmon band centered at around 800 nm in the nanorod spectra. The observed agglomeration indicates a decomposition of the nanorod surface ligands under pulsed laser irradiation that results in a decrease of colloidal stability.The observed spectral changes can be attributed to two main effects. Surface meltingAlthough the nanorods show some morphological restructuring and agglomeration, we emphasize that both the UV-Vis data and the gel studies confirm that the sample still contain a substantial fraction of resonant nanorods under the chosen irradiation conditions.6 relative light units (RLU). We performed the inactivation studies with PEGylated nanorods as well as with rods functionalized with annexinV that binds to phosphatidylserine (PS) of the enveloped MLV. For the latter, Ca2+ was added to the binding buffer when incubating annexinV-functionalized nanorods with virus particles to achieve a final Ca2+ concentration of 2 mM.In a typical virus inactivation experiment, PEGylated nanorods were incubated with MLV particles in a ratio of more than 10000:1 in a total volume of 67 μL at 4 °C for up to 12 h. The samples were then diluted by adding 933 μL of PBS, pH 7.4 to a total volume of 1 mL. The final virus concentration was such that infections of Rat2 reporter cells with the luciferase encoding recombinant viruses resulted in approximately 1 × 10In many applications it is necessary to inactivate the virus in a complex biological matrix. For instance, virus inactivation plays a critical role in the pharmaceutical industry for the fabrication of monoclonal antibodies (mAbs). We emulated realistic process conditions by performing the virus inactivation in an IgG antibody  containing Tris solution as biological matrix. The proteins were added after overnight co-incubation of nanorod and virus.In a first set of experiments, we tested the hypothesis that resonant plasmonic nanorods enhance fs pulsed laser driven virus inactivation. To that end, virus samples were irradiated for 10 s with 805 nm laser pulses with a width of 35 fs in the presence and absence of pegylated nanorods. All samples contained IgG antibodies. Figure In a second set of experiments, we used the maximum average laser power of 3 W and measured viral inactivation in the presence of three different nanoparticles: virus + PEGylated nanorods; virus + annexinV-functionalized nanorods; virus + spherical nanoparticles. Unlike for the nanorods, the LSPR of the 40 nm diameter gold nanoparticles (530 nm) did not overlap with the exciting laser pulse. The nanorod and nanoparticle to virus ratios were both higher than 10000:1. Additional controls included laser irradiation of viruses without nanoparticles. After laser irradiation for 10 s, virus infectivity was quantified Fig. . The 805We tested for potential collateral damage to IgG antibodies through laser irradiation  of PEGylated and annexinV functionalized nanorods through ELISA Fig. . This tiOne unexpected finding from Fig. The fact that annexinV fails to enhance virus inactivation and the absence of a significant non-specific binding to MLV in the case of the PEGylated nanorods suggests that a direct binding between nanorods and virus particles is not required for the nanorod-enhanced photonic virus inactivation.The LRVs measured in Fig. 11 particles/mL, which corresponds to one rod in a cube of solvent with side length of approximately 2 μm, we can exclude that virus particles and nanorods co-localize close enough to generate a sufficient E-field enhancement to impact ISRS or multiphoton absorption of the virus. For similar reasons, it is unlikely that thermal effects are the underlying cause of the observed virus inactivation. Although the resonant fs laser excitation induces a temperature jump in the nanorod and its immediate environment, this effect is local , superoxide anion (O2−), or hydroxyl radical (•OH)39. Even if their formation is limited to the immediate vicinity of the nanorods, the ROS can diffuse in solution. Singlet oxygen, for instance, has a typical diffusion length in water of approximately 200 nm40. If these reactive species result in the disabling of important surface groups required for binding to and uptake into host cells, they could – in principle – account for the observed MLV inactivation. To test whether these ROS were involved in the virus inactivation, we repeated the fs laser irradiation of a mix of MLV and resonant nanorods in the presence of ROS scavengers. In particular, we used sodium azide (scavenger for 1O2), MnTBAP (scavenger for O2−), mannitol (scavenger for •OH)42. While the concentration of ROS scavengers used in these experiments did not show any cytotoxicity (data not shown), addition of ROS scavengers did not suppress nanorod mediated virus inactivation . It has been demonstrated in previous studies that plasmon excitation in gold nanocubes can generate singlet oxygen (ion Fig. , suggest44. Intense pressure wave generation is expected to dominate only for very short pulse durations as used in this work. We emphasize that although Tsen and coworkers dismissed the pressure wave argument in their studies due to insufficient laser power, the situation is fundamentally different in our case due to the presence of the plasmonic nanoparticles, which we expect to greatly reduce the power threshold for shockwave generation. Based on published analyses of threshold intensities in the presence of nanorods45, we estimate that average powers ≥0.3 W are sufficient to trigger shockwaves under our experimental conditions using pulse durations of 35 fs. We recorded the photoacoustic response of the nanorods, which represent a broad band acoustic emissions followed by a gradual fluctuation that decreased to near zero until another distinct oscillation arrives (Fig. Another potential virus inactivation mechanism that does not require direct contact between the virus and the nanorods is plasmonically-enhanced shockwave generation. The duration of the incident pulse is crucial in determining the feasibility of inactivationves Fig. . AlthougIndependent of the exact physical mechanism that causes the plasmonic enhancement of virus inactivation, it is key to establish which stage of the viral infection is affected by it. Since TEM inspections after laser exposure did not reveal obvious morphological changes in the virus samples, we hypothesized that the effect is primarily caused by molecular-level perturbations of the MLV membrane and/or surface groups, which prevents an effective binding to the host cell and subsequent fusion. To test this hypothesis, we repeated the fs laser irradiation of MLV/luc particles containing S15-BlaM fusion protein in presence and absence of resonant nanorod. Figure We have demonstrated the enhancement of fs-pulsed NIR radiation induced photonic virus inactivation through plasmonic nanoparticles. Irradiation in the presence of resonant nanorods significantly reduced viral fusion with the host cell, suggesting that the plasmonic enhancement acts on viral surface functionalities responsible for early stages of the viral infection rather than on the viral genome or enzymes. LRVs of ≥3.7 were achieved with MLV in as little as 10 s of irradiation. The inactivation was highly specific to the virus while co-incubated IgG antibodies did not show any loss in functionality. The ability to enhance the efficacy of selective photonic virus inactivation with NIR radiation through plasmonic nanoparticles paves the path to a broader applicability of the technique in research and technology.Supplementary Information