Oncobox Atlas of Normal Tissue Expression (ANTE). Our data will be useful to all those working with the analysis of human gene expression.Comprehensive analysis of molecular pathology requires a collection of reference samples representing normal tissues from healthy donors. For the available limited collections of normal tissues from postmortal donors, there is a problem of data incompatibility, as different datasets generated using different experimental platforms often cannot be merged in a single panel. Here, we constructed and deposited the gene expression database of normal human tissues based on uniformly screened original sequencing data. In total, 142 solid tissue samples representing 20 organs were taken from post-mortal human healthy donors of different age killed in road accidents no later than 36 hours after death. Blood samples were taken from 17 healthy volunteers. We then compared them with the 758 transcriptomic profiles taken from the other databases. We found that overall 463 biosamples showed tissue-specific rather than platform- or database-specific clustering and could be aggregated in a single database termed   Growing amount of transcriptomic data is deposited in the special public repositories like Gene Expression Omnibus, GEO8 and Array-Express9 which have already accumulated over two million individual transcriptomic profiles obtained in over 100,000 series of experiments10. The data cover a wide spectrum of specific human physiological conditions, including most of known diseases and developmental features12.High throughput gene expression (transcriptomic) analyses can be used in every aspect of biomedicine17. The NGS methods have become the standard in the field of gene expression studies because of higher reproducibility and lower platform bias18.The enclosed transcriptional profiles were obtained using different experimental platforms of either microarray hybridization or next-generation sequencing (NGS) of mRNA. However, the gene expression may be poorly comparable across the different platforms because of use of different equipment and reagents20. Ideally, they should represent normal tissues from healthy donors, profiled in a single series of experiments using the same equipment and reagents. Nowadays, there is a shortage of such gene expression data. The largest published dataset, GTEx21 , lacks publicly available data on the donors’ age, and this puts limits on data analysis and makes impossible age-matched studies, which are crucial for many practical applications and aging research. For that reason, we didn’t include GTEx data in this study.Comprehensive studies of molecular pathology or tissue specific patterns require a collection of reference samples22 (625 samples), ENCODE23 polyA RNA-seq (38 samples), and ENCODE total RNA-seq (89 samples). However, they lack one or several of the previously mentioned features. For example, in The Cancer Genome Atlas (TCGA) project database, specimens of histologically normal tissue adjacent to surgically removed tumors24 are considered normal. However, these tissues may not be completely normal due to numerous effects tumors may have on the neighboring cells, including biased growth factors and cytokine balances25, pathological inflammation26, and altered vascularization27. The ENCODE polyA RNA-seq and ENCODE total RNA-seq datasets were generated based on the normal tissues subjected to NGS using different library preparation methods. They have only 1–4 samples profiled per tissue type  and most of the cases can not form a statistically significant reference group.The other relevant databases of significant size do include the information on the donors’ age: TCGA28. We also compared our data for consistency with the transcriptomic profiles taken from databases The Cancer Genome Atlas (TCGA), ENCODE polyA RNA-seq, and ENCODE- total RNA-seq. We found that 463 biosamples showed tissue-specific rather than platform- or database-specific clustering. These have beeen aggregated in a single database named Oncobox Atlas of Normal Tissue Expression (ANTE) , including 11 sex-matched statistically significant tissue groups. Our data will be useful to all those working with the analysis of human gene expression.During our study we have designed and assembled the gene expression database of normal human tissues based on uniformly obtained original sequencing data using Illumina HiSeq-3000 engine. A total of 142 solid tissue samples representing 20 organs were taken from post-mortem human healthy donors, who had died in road accidents, no later than 36 hours after death. Blood samples were taken from 17 healthy volunteers. The materials, that had been being collected since 2012, were stored until gene expression profiles were obtained in one series of experiments using the same reagents and protocols. The gene expression profiles were then submitted to Gene Expression Omnibus under accession id GSE120795In the period from March 2012 to May 2018, we obtained 142 solid tissue samples from 20 human organs at the Department of Pathology at the Faculty of Medicine, Moscow State University, Russia, from autopsies taken from 23 non-related adult healthy donors killed in road accidents, no later than 36 hours after death. We also collected normal blood samples from 17 healthy volunteers. For each biosample an informed written consent to participate in the study was obtained from the patient’s legal representative. The consent procedure and the design of the study were approved by the ethical committees of the Faculty of Medicine, Moscow State University, and of the National Research Center for Hematology. The biosamples were evaluated by a pathologist to confirm the tissue origin of every specimen prior to analyses.Overall, blood and solid tissues were taken from 8 male and 9 female and 14 male and 9 female donors, respectively. The mean age was 33.47 years old (range 23–75 y.o.) and 37.39 y.o. (12–54 y.o.), respectively. The full list of the tissues and biosamples obtained is given in Online-only Table Solid tissue samples were either immediately stabilized in RNAlater  and then stored at −70 °C or fixed in formalin and embedded in paraffin blocks. RNA extraction was performed immediately before the preparation of sequencing libraries using QIAGEN RNeasy Kit (Qiagen) or Direct-zol™ RNA MiniPrep (Zymo Research) with TRI Reagent (MRC) for tissues in RNAlater and the RecoverAll™ Total Nucleic Acid Isolation Kit for FFPE (Invitrigen), following the manufacturer’s protocol. In cases of whole blood normal samples, mononuclear cells were extracted shortly after peripheral blood collection. Alternatively, a fraction of CD138 + cells was isolated from bone marrow with Ficoll Paque Plus (Sigma) followed by enrichment using CD138 MicroBeads (Miltenyi Biotec) and MS Columns (Miltenyi Biotec). Cells were counted by Scepter™ 2.0 Handheld Automated Cell Counter (Merck Millipore) and immediately subjected to RNA extraction. For RNA extraction, cells were resuspended in TRI Reagent (MRC) and then Direct-zol™ RNA MiniPrep (Zymo Research) was used for the RNA extraction. RNA was quantified using Nanodrop (Thermo Fisher Scientific), ethanol-precipitated, and stored in liquid nitrogen until sequencing.RNA Integrity Number (RIN) was measured using Agilent 2100 bioanalyzer. Agilent RNA 6000 Nano or Qubit RNA Assay Kits were used to measure RNA concentration. KAPA RNA Hyper with RiboErase (KAPA Biosystem) Kit was used for further depletion of ribosomal RNA and library preparation. Different adaptors were used for multiplexing samples in one sequencing run. Library concentrations and quality were measured using Qubit ds DNA HS Assay kit (Life Technologies) and Agilent Tapestation (Agilent). RNA sequencing was performed using Illumina HiSeq 3000 equipment for single end sequencing, 50 bp read length, for approximately 30 million raw reads per sample. Data quality check was conducted using Illumina SAV. De-multiplexing was performed using Illumina Bcl2fastq2 v 2.17 software.30 in ‘GeneCounts’ mode with the Ensembl human transcriptome annotation (Build version GRCh38 and transcript annotation GRCh38.89). Ensembl gene IDs were converted to HGNC gene symbols using Complete HGNC dataset . The mapping statistics for corresponding dataset can be found on Figshare29 in the file “QC and additional meta information”. The available RNA sequencing profiles for normal and cancer tissues matched normal samples were extracted from the websites of projects TCGA and ENCODE . Combined meta information for compatible gene expression profiles from different databases can be found on Figshare29 in the file “ANTE overview”.Gene expression profiles were deposited at the Gene Expression Omnibus database (GEO) under accession number GSE120795FFPE or tissue in RNAlater for solid tissue, and RNA in ethanol for blood samples.To assess if the obtained gene expression profiles are in correlation with the biological nature of the biosamples tested and identify samples that might be of low quality, we performed cluster analysis of all the RNA sequencing data we had obtained Fig. . The colThe FFPE and RNAlater samples formed several mixed clusters on the dendrogram, which suggests that the clustering was independent of the sample preparation technique for solid tissues. The blood samples formed a clearly distinct cluster on the left side of the dendrogram, which is in line with the histological status of this tissue Fig. , which sHowever, we then observed a mixed cluster next to the one formed by the blood samples, which included both blood and solid tissue specimens Fig. , red, an29 in the file “QC and additional meta information”.The established threshold effectively marked samples with low quality values of other QC metrics, e.g. proportion of genomic counts, high rate of mismatches, number of reads spanning splice junction, high percentage of ribosomal counts. Full list of mapping statistics generated by STAR aligner and additional QC metrics generated by NCBI MAGIC is available on Figshare(i)RIN, that shows the level of RNA degradation (lower RIN points to more degraded RNA). All samples with high RIN RIN > 4) passed the QC RNA concentration. We found no correlation between RNA concentration and number of uniquely mapped reads Fig. . TherefoWe then looked for a correlation between whether a biosample passes the QC and its internal characteristics. The following parameters were investigated:Only the samples that had more reads than the QC threshold were analyzed in further comparisons.Finally, we assessed the reproducibility of the RNA sequencing output data for the characterization of normal human tissues. We performed RNA sequencing of four different fragments of each of the following tissue specimens: two human liver (ID 16_5) and esophagus (ID E_3). The tissue fragments were blinded and sent for sequencing separately. In each case, one of quadruplicates was sequenced and mapped in a separate batch. In both cases we observed high pairwise correlation coefficients between quantile normalized gene expression values  Fig. . We conc22 of ‘normal’ tissues adjacent to tumors , ENCODE23 database, poly(A) priming library preparation , and ENCODE23 database, random priming library preparation . All the above mentioned gene expression profiles, both obtained in our experiments and published earlier, were merged and quantile normalized34. We then performed cluster analysis of these data and found that both ENCODE databases showed clustering similar to that of the current experimental database, with clear tissue specific, rather than database specific, clustering patterns . The database overview is presented in the Table 29 in the file “ANTE overview”. In total, the ANTE database contains 463 transcriptomic profiles for 11 tissue types. All the types of tissue are represented by seven samples or more, with the mean representation of 42 samples per tissue.After that we checked if our gene expression data are compatible with previously published transcriptomic datasets. The largest published datasets of RNA sequencing data for normal tissues were TCGA databaserns Fig. . Contrarrns Fig. , probablrns Fig. . We thenOncobox Atlas of Normal Tissue Expression (ANTE). The database includes 67 original experimental and 396 previously published gene expression profiles for 11 normal human tissues. The experimental profiles that are published here for the first time can be considered a golden standard data from the histopathological point of view as they had been obtained for the post-mortem human healthy donors, killed in road accidents, no later than 36 hours after death. Blood samples were taken from 17 healthy volunteers. The ANTE database provides unparalleled source of normal human tissues for transcriptomic research. The data in the database are in a machine-readable format and annotated by the available patients’ data which include tissue type, sex, and age of a donor. Besides comparisons of individual gene expressions, e.g. of pathological v normal human tissues, this collection of molecular data could be beneficial for a more complex level of data analysis such as molecular pathway activation scoring37 and bioinformatic ranking of drugs38. Additionally, the database can be used to revise lists of tissue specific gene expression biomarkers and housekeeping genes.We have assembled the gene expression database of normal human tissues termed Download metadata file


Members of the candidate phylum Acetothermia are globally distributed and detected in various habitats. However, little is known about their physiology and ecological importance. In this study, an operational taxonomic unit belonging to Acetothermia was detected at high abundance in four full-scale anaerobic digesters by 16S rRNA gene amplicon sequencing. The first closed genome from this phylum was obtained by differential coverage binning of metagenomes and scaffolding with long nanopore reads. Genome annotation and metabolic reconstruction suggested an anaerobic chemoheterotrophic lifestyle in which the bacterium obtains energy and carbon via fermentation of peptides, amino acids, and simple sugars to acetate, formate, and hydrogen. The morphology was unusual and composed of a central rod-shaped cell with bipolar prosthecae as revealed by fluorescence in situ hybridization combined with confocal laser scanning microscopy, Raman microspectroscopy, and atomic force microscopy. We hypothesize that these prosthecae allow for increased nutrient uptake by greatly expanding the cell surface area, providing a competitive advantage under nutrient-limited conditions. Microorganisms drive the major biogeochemical nutrient cycles, which are fundamental for many biotechnological processes and directly linked to our health –3. CultuCandidatus Fermentibacter daniensis (candidate phylum Hyd24-12) [Candidatus Promineofilum breve (phylum Chloroflexi) [The fast developments in next-generation sequencing and metagenomics enable the characterization of the whole community gene pool and can be used to elucidate the functional potential of individual microbial members. This allows us to better understand the ecological roles and interactions of the ubiquitous uncultivated microorganisms –16. Genoyd24-12) , OP9/JS1yd24-12) , and Canroflexi) .2 fixation and have an acetogenic lifestyle. Accordingly, it was given the name Candidatus Acetothermum autotrophicum. Another MAG (Acetothermia bacterium 64_32) was extracted from a marine shelf siliciclastic sandstone deposit from an oil reservoir [2 fixation pathways, indicating a heterotrophic lifestyle. Other physiological information about this candidate phylum is currently not available.In one of our studies of anaerobic sludge digesters , a metageservoir . This drAcetothermia bacteria occupy diverse habitats and have been detected in several geographically separated anaerobic digesters Figure , suggestBetween 1 and 10 biomass samples were obtained from each of 31 anaerobic digesters treating primary and surplus sludge at 18 Danish wastewater treatment plants (WWTPs) in the period from 2011 to 2017 , following the manufacturer’s protocol (LSK-108) without the optional DNA shearing and DNA repair steps. The library was loaded on a FLO-MIN106 flow cell and sequenced using the MinION Mk1B DNA sequencer (Oxford Nanopore Technologies). The sequencing software used was MinKNOW v. 1.7.3  with the 48-h sequencing workflow (NC_48 h_Sequencing_Run_FLO_MIN106_SQK-LSK108.py). Sequencing reads were base-called using Albacore v. 1.2.1 .The SSPACE-LongRead scaffolder v. 1.1  was usedPhylogenetic analysis and fluorescence in situ hybridization (FISH) probe design were performed using the ARB software package  with theFresh biomass samples, taken from sludge digesters at Randers and Esbjerg WWTPs, were treated with either ethanol or paraformaldehyde (PFA) for the optimal fixation of Gram-positive and Gram-negative bacteria, respectively. FISH was performed on fixed samples as detailed by Daims et al. . The hybCells hybridized with newly designed probes were observed by a white light laser confocal microscope (Leica TCS SP8 X). Targeted cells were further characterized by Raman microspectrometry using a Horiba LabRam HR 800 Evolution system  equipped with a Torus MPC 3000 (UK) solid-state semiconductor laser, and higher resolution information on the cell shape was further obtained by atomic force microscopy (AFM) from Syto9-stained cells, using a JPK Nanowizard IV system  on an inverted Zeiss Axiovert 200 M epifluorescence microscope. The detailed procedures and equipment information are supplied in Supplementary Method The raw amplicon sequencing reads, metagenome reads, and the annotated genome sequence data have been submitted to the European Nucleotide Archive (ENA) under the study accession number PRJEB22104.Acetothermia bacteria have previously been observed in anaerobic digesters , but theOnly a single operational taxonomic unit (OTU) assigned to phylum Acetothermia was observed in four mesophilic sludge digesters at two WWTPs from the survey of 31 digesters Fig. . The twoTo learn more about the ecophysiology of Acetothermia bacteria in anaerobic digesters, we sought to obtain genomic information from the organism represented by the abundant OTU. This organism was consistently found in high abundance in a full-scale anaerobic sludge digester at Randers WWTP, thus providing a good target-system for in-depth investigations Fig. . To thisRan1 was classified to the Acetothermia phylum based on its 16S rRNA gene using the SILVA taxonomy. Phylogenetic analyses of the available sequences for this phylum revealed evident separation of lineages with similar ecological preferences and habitats Fig. . The 16SCaulobacter and Asticcacaulis [To investigate the morphology of Ran1, we designed two FISH probes that cover the proposed novel genus that contains Acetothermia bacteria associated with anaerobic digesters Fig. . These pcacaulis . Such apcacaulis .Caulobacter [Asticcacaulis [Further analysis of FISH data demonstrated three different morphologies according to the size of the central rod and the length or appearance of the polar prosthecae: (1) central rod with bipolar prosthecae of similar length; (2) smaller central rod with bipolar stalks of different length; (3) smallest central rod with a single polar prostheca Fig. . These dlobacter  and Asticacaulis .Higher resolution information on cell surface properties of Ran1 was obtained using AFM Fig. . AFM con2) and SA/V become 42% larger (from 9.6 to 13.7 μm−1), providing an increased interface for nutrients uptake [Caulobacter inversely correlates with the availability of phosphate, indicating enhanced phosphate uptake capability [4−P/L), compared with the other digesters (95 ~ 480 mg PO4−P/L)  as well as concentration of organic compounds (VFAs) in the liquid phase  and surface area to volume ratio (SA/V) were calculated for the rod-shaped cell with and without the prosthecae, based on the observed average length and width. Results show that development of the prosthecae made the SA increase by 3.5 times  Table . Furthere Figure  and S8. Some cell envelope properties can be inferred directly from genomes, based on the presence or absence of cell envelope genes found specifically in archetypical monoderm or diderm lineages , which aCaulobacter crescentus, bactofilins are found as membrane-associated clusters at the pole of the cell, where they recruit the peptidoglycan synthase PbpC and initiate prosthecae development [Further genome annotation and specialized searches using the PilFind program  did not elopment . It is, To learn more about the potential function of Ran1, we constructed a metabolic model based on the annotated genome Fig. . A briefSeveral ABC transporter genes were detected, including those for importing amino acids, peptides, glycerol-3-phosphate, maltose, ribose, and alpha-glucoside. This indicates that Ran1 can take up these compounds at the expense of ATP or the proton motive force (PMF) and use them as carbon and energy sources.Sugars imported can be catabolized through the Embden–Meyerhof–Parnas pathway. The ATP produced during the transformation of hexoses to pyruvate can provide the cells with energy. Besides hexoses, Ran1 may utilize a broad range of pentoses, as it has all the genes of the non-oxidative pentose phosphate pathway . Ran1 alporABC), generating reduced ferredoxin (Fdred). Acetyl-CoA can then enter the fermentation pathway catalyzed by two acetyl-CoA synthetases (acsA or acdA), resulting in the production of acetate and energy in the form of ATP.The pyruvate generated from sugars can be converted to acetyl-CoA by the pyruvate:ferredoxin oxidoreductase complex  or 2-ketoglutarate ferredoxin oxidoreductase (kor) to generate acetyl-CoA or succinyl-CoA, which can then be cleaved to yield acetate or succinate and energy in the form of ATP [red). Some key enzymes involved in the catabolism of branched-chain amino acids were absent in the annotated genome  and the methyl viologen reducing hydrogenase  [+/H2 with NAD(P)H/NAD(P)+ [red/Fdox [+ or Na+ to generate PMF, using the energy produced from hydrolysis of pyrophosphate [2 and acid products (formate and acetate) generated from fermentation can be utilized by the hydrogenotrophic Methanolinea and acetotrophic Methanosaeta in the system  Fig.  and S12,oduction , 62. It ion [red . The pro/NAD(P)+ , 65 and red/Fdox , respecthosphate . The H2 tem Fig. .Clostridium acetobutylicum [Clostridium perfringens [Surprisingly, the genome does not encode any conventional ATP synthases, which are often used to generate ATP at the expense of the established PMF . Loss ofutylicum  and Closfringens . The enefringens .The genome possesses several genes typical of anaerobic bacteria, such as the oxygen-sensitive class III ribonucleoside triphosphate reductase, ferredoxin oxidoreductases, and radical S-adenosyl-methionine-dependent proteins , and as a provider of precursor substances  for methanogens (like the acetotrophic Methanosaeta and hydrogenotrophic Methanolinea) which coexisted in the ecosystem at high abundance . The bacterium was stably present in several mesophilic sludge digesters during a period of several years and represents a novel genus that includes other previously detected 16S rRNA gene sequences of Acetothermia in anaerobic bioreactors. The metabolic reconstruction suggested that it is an anaerobic, fermentative bacterium involved in acidogenesis, producing organic acids (such as acetate and formate) and hydrogen from the fermentation of peptides, amino acids, and simple sugars . Interestingly, this Acetothermia bacterium demonstrated an unusual morphology composed of a central rod cell and long prosthecae protruding from both poles of the rod. It is the first time this type of morphology has been shown for a bacterium outside the class Alphaproteobacteria, which can shed new light on the evolution of cell morphology. The long and flexible prosthecae greatly expand the surface area of the cell and provide increased access to nutrients under nutrient-limiting conditions. This is supported by their abundance being restricted to digesters with relatively low levels of phosphorus and other nutrients. The genome generated in this study is one of the few closed genomes for uncultured candidate phyla and importantly provides the foundation for future study on pathway expression of the lineage with metatranscriptomics and metaproteomics. The design of FISH probes for the genus will facilitate future in situ studies of the genus in other systems.Phylogenetic analyses of the Ran1 genome classified it as a novel genus within the previously described Acetothermia phylum. We suggest that the closed genome should serve as the type material for this genus , 73 and Candidatus Bipolaricaulis gen. nov.Bipolaricaulis .Candidatus Bipolaricaulis anaerobius sp. nov.Bipolaricaulis anaerobius .“Candidatus Acetothermus” [Acetothermus was already the name of a valid genus within the phylum Bacteroidetes [Candidatus Acetothermum” and “Candidatus Acetothermus” interchangeably within the original publication [Candidatus Bipolaricaulis anaerobius instead be made the type genus for the phylum and the name be changed accordingly to Candidatus Bipolaricaulota (the phylum of the genus Candidatus Bipolaricaulis).In addition, we would like to propose that the encompassing Acetothermia phylum be renamed. The phylum takes its name from the type genus thermus” . Howeverroidetes , 75, maklication . To prevSupplementary InformationData Set1Data Set2Data Set3


Poly (vinylidene fluoride) nanofibers (PVDF NFs) have been extensively used in energy harvesting applications due to their promising piezoresponse characteristics. However, the mechanical properties of the generated fibers are still lacking. Therefore, we are presenting in this work a promising improvement in the elasticity properties of PVDF nanofibrous membrane through thermoplastic polyurethane (TPU) additives. Morphological, physical, and mechanical analyses were performed for membranes developed from different blend ratios. Then, the impact of added weight ratio of TPU on the piezoelectric response of the formed nanofibrous composite membranes was studied. The piezoelectric characteristics were studied through impulse loading testing where the electric voltage had been detected under applied mass weights. Piezoelectric characteristics were investigated further through a pressure mode test the developed nanofibrous composite membranes were found to be mechanically deformed under applied electric potential. This work introduces promising high elastic piezoelectric materials that can be used in a wide variety of applications including energy harvesting, wearable electronics, self-cleaning filters, and motion/vibration sensors. Alternative energy sources , such asThere are several methods that can be used to fabricate the PVDF nanofibers and their nanocomposites. The most common and controlled technique is electrospinning ,21,22,23Among various composite nanofibrous materials, thermoplastic polyurethane has a great potential in many applications where high mechanical characteristics are required ,32. Thes−1) at room temperature.A parallel bicomponent TPU/ Polyimide (PI) membrane with enhanced mechanical strength has been introduced as an electrolyte for the lithium ion battery . The strIn our work, we are providing a composite of poly (vinylidene fluoride) as a piezoelectric polymer and polyurethane as a thermoplastic elastomer, in order to achieve a high mechanically robust mat for piezoelectric applications (piezoelastic NFs). The effect of thermoplastic polyurethane (TPU) addition with different ratios on the morphological structure and mechanical analysis of PVDF nanofibers was investigated, while the physical and structural properties of PVDF/TPU composite nanofiber including scanning electron microscope (SEM), Fourier transforms (FT-IR), and X-ray diffraction (XRD) analysis were introduced. The piezoelectric properties of PVDF/TPU composite nanofiber were studied through both impulse and compression loading analysis and piezoforce microscopy.®, King of Prussia, PA, USA) was supplied by ARKEMA and thermoplastic polyurethane (TPU) with Polydispersity Index (PDI) of 1.83 and 107,020 g mol−1 molecular weight was supplied by . Known polymer concentrations were dispersed in dimethylformamide .Polyvinylidene fluoride (PVDF)  through polymer blending for 24 h before the electrospinning process.Electrospinning was performed by adding 5 mL of polymer solution into a plastic syringe tipped with a stainless steel needle. The positive voltages were provided from a high voltage power supply CZE1000R  to the metallic needle with gauge 18, for application of voltages around 25 kV with constant feed rate of (1 mL/h) using a NE1000 syringe pump . Needle-to-collector distance was 10 cm. Random PVDF/TPU nanofibers composite was collected on a drum collector covered with aluminum foil and connected to the ground.The morphology of PVDF/TPU nanofibers (NFs) was observed by scanning electron microscope  with an accelerating voltage of 15 kV. The nanofiber mats were placed on a carbon tape fixed on aluminum stubs and sputter coated with platinum. The diameter of NFs was analyzed using Image-J software . The average fiber diameter distribution was manually detected by measuring the length through fiber boundaries at different imaging scales .−1 over a range of 4000–400 cm−1.The crystal phase of NFs was obtained with an X-ray diffractometer (XRD)  with Cu Kα (1.5 Å) radiation over Bragg angle from 10° to 90°. The β phase content was calculated with the aid of a Fourier transform infra-red spectrometer (FT-IR)  in ATR mode. Samples were scanned 120 times at a resolution of 5 cmTesting the effect of TPU addition into the PVDF mechanical properties was performed by cutting the nanofiber mat into rectangular pieces (1 × 6 cm). The samples were placed between two cardboard holding frames with gauge length of 4 cm as shown in Piezoelectric voltage signals were detected from the synthesized PVDF/TPU nanofibers mats through a simple set-up of an impulse loading test, as shown in In this part, mechanical pressure was applied through a spring which was controlled by an electric motor that could control the pressure frequency of the applied spring in a range of a few Hz. Regarding force control, the spring compression was controlled and mapped to corresponding force values. The spring plunger had a circular light-rubber disc of 2 cm diameter. The nanofibers mat was then sandwiched between two foil sheets and the generated voltage detected through the same high impedance oscilloscope, as mentioned in The formed nanofiber mats of different PVDF/TPU blends ratios were analyzed using an atomic force microscopy (AFM) system MFP-3D  with a single-frequency piezoresponse force microscope (PFM) contact mode at the Center of Advanced Materials (CAM), Qatar University, Doha, Qatar. In this characterization, the mechanical surface deformation had been measured under applied electric voltages. To excite the sample with the electric signal, a conductive tip with platinum-deposited cantilever AC240TM  had been used. The tip, of 2 N/m spring constant and 70 kHz resonance frequency, was first calibrated using thermal GetRealTM mode to obtain an exact value of the spring constant and accurately convert the raw signal in (V) to picometer (pm) with applying voltage range from 1 V up to 10 V, and the subsequent surface roughness amplitude response was recorded and evaluated using Igor Pro 6.37 software .PVDF/TPU composite nanofibers morphology was examined by Field Emission Scanning Electron Microscope (FESEM). From the respective micrographic images, quantitative analysis of fiber diameter and diameter size distribution was conducted. Average fiber diameter of nanofibers for all samples was calculated by ImageJ as represented in The effect of TPU addition on the morphological structure of PVDF/TPU nanofibrous composites was investigated. It was noticed that larger fiber diameter and wide diameter size distribution resulted from pure TPU and PVDF/TPU nanofibrous composites compared to the pure PVDF. The average fiber diameter of pure PVDF nanofibrous composite membrane was 110 nm while the average fiber diameters of PVDF/TPU (1:1) and pure TPU were 311 nm and 275 nm respectively.−1. Moreover, the absorption modes for the β-phase at 840 cm−1 appeared strongly for PVDF nanofibers and decreased with increasing the TPU concentration, which was consistent with the decreasing of piezoelectric response with the addition of TPU. The relative amount of β phase has been quantified by considering the relative absorption intensity of β phase at 840 cm−1 and α phase at 760 cm−1 according to the proposed equation by Gregorio and Cestari [−1 respectively. By calculating the previous equation according to the obtained IR curves, the β-phase content for the PVDF nanofiber is 0.75, which confirms the high piezoelectric response of pure PVDF, while a noticeable decrease in the β-phase is observed with increasing the TPU concentration to 0.48 for PVDF:TPU (1:3) nanofiber.The FT-IR spectra of nanofibrous composite membranes are shown in  Cestari ,44:F (β)The XRD graph b revealsIn order to explore the mechanical properties of the newly developed composite, a tensile strain test was conducted and the recorded stress-strain curve is presented in As it can be seen in Toughness of nanofibrous composites membranes was calculated from the area under the stress-strain curves. As known, toughness is the ability of material to absorb energy and deform without fracture. It can be obviously noticed that by increasing the ratio of TPU, toughness is increased. This means that the developed membranes are getting more elastic and able to absorb more energy. As mentioned earlier, this can be explained by the excellent mechanical properties of TPU which is considered as one of the elastomer polymers.Regarding the piezoelectric measurements, In this section, different operated voltages were applied through a conductive tip to form sensitive mechanical deformations detected by PFM. Based on SEM morphology study, the increase in diameter with increasing the TPU concentration can be attributed to the higher molecular weight of TPU polymer which leads to higher viscoelastic force of the spinning solution. Similar results are consistent with our finding that the increase in the molecular weight consequently increases the resultant fiber diameter due to a higher number of chain entanglements and increased viscosity . Koski eAlthough there was enhancement of mechanical properties by increasing TPU, the generated potential and correlated sensitivity were found to be reduced which proves that the PVDF ratio with included polarizations and beta-sheets was dominant in generating electric potential under mechanical pressure excitation. Similar results have confirmed our findings by calculating the piezoelectric coefficient of PVDF/TPU blended NFs for wound healing . The resRegarding PFM analysis, it can be concluded that a little addition of TPU elastomer polymer can enhance the mechanical response (elastic response) according to applied electric potential with most of polarizability inside PVDF still kept sensitive to the applied voltage. By increasing TPU ratio over 50%, the composite loses the polarizability and piezosenstivity starts to significantly decrease. So, it can be clarified that the excellent elastic properties of TPU helped the mechanical deformation of PVDF/TPU nanofibrous composite membranes to be tremendously developed through more flexibility of the motion of electric dipoles inside the composite nanofiber under the exposure of applied electric excitation.In this paper, we have presented a newly developed nanocomposite of PVDF nanofibers blended in-situ with TPU. The results showed that normally distributed and beads-free nanofibers were obtained in all cases as a result of optimized spinning conditions and homogenous polymer blending. β-phase was found to be 0.75 for the pure PVDF nanofiber which confirms the high piezoelectric response of it, while significant decrease in the β-phase was observed with increasing the TPU concentration to 0.48 for PVDF:TPU (1:3) nanofiber. The main peaks of β phase that resulted from the XRD and FT-IR analysis of different blend ratios of PVDF/TPU nanofibrous composite membranes confirms the piezoelectric behavior of PVDF/TPU composites as well. The addition of TPU improves the mechanical properties of the nanofibrous composite membrane with maximum breaking strain up to 75%. However, it reduces the piezoresponse sensitivity of PVDF nanofibrous composite membranes. Blended compositions of PVDF/TPU 1:1 and 3:1 can be considered as the optimum blend ratio and lead to a quiet trade-off between mechanical and piezoresponse characteristics. In addition, the mechanical deformations of different blend ratios of the developed nanofibrous composite membrane have been analyzed under different applied electric potentials. The blended PVDF/PU (1:1) was found to have highest mechanical surface deformation at applied 10 V, which results from more flexibility in dipole excitations inside PVDF due to the elastic content of TPU. This work is promising to develop a high elastic piezoresponse membrane that can be used in different applications such as energy harvesting, biomedical, self-cleaning filters membranes, and sensing applications.


Using lipid-SIP, we found that methylotrophic methanogens incorporate 60–86% of dissolved inorganic carbon (DIC) into lipids, and thus considerably more than what can be predicted from known metabolic pathways (~40% contribution). In slurry experiments amended with the marine methylotroph Methanococcoides methylutens, up to 12% of methane was produced from CO2, indicating that CO2-dependent methanogenesis is an alternative methanogenic pathway and suggesting that obligate methylotrophic methanogens grow in fact mixotrophically on methyl compounds and DIC. Although methane formation from methanol is the primary pathway of methanogenesis, the observed high DIC incorporation into lipids is likely linked to CO2-dependent methanogenesis, which was triggered when methane production rates were low. Since methylotrophic methanogenesis rates are much lower in marine sediments than under optimal conditions in pure culture, CO2 conversion to methane is an important but previously overlooked methanogenic process in sediments for methylotrophic methanogens.Methyl substrates are important compounds for methanogenesis in marine sediments but diversity and carbon utilization by methylotrophic methanogenic archaea have not been clarified. Here, we demonstrate that RNA-stable isotope probing (SIP) requires  Although the underlying mechanism is beyond the scope of the current study, methylotrophic methanogens in our incubations could take advantage of hematite as potential electron conductor [Members of the genus  genomes , 77 rulilow Fig. . Apparenonductor , 49 or honductor  as indic2 during methylotrophic methanogenesis of M. barkeri  without the addition of H2 [2 by M. methylutens  in our study (Table 2 (10%) , which is linked to CO2 assimilation. This finding strongly suggests that the alleged obligate methylotroph studied here was rather mixotrophically converting both available substrates  to methane. Our detailed labeling studies showed that the kinetics of substrate utilization apparently is a decisive factor in channeling more or less CO2 into the pathway of methanogenesis: more methane formed from CO2 when the overall kinetics were slow, and vice versa. From an ecological perspective, DIC is a much more pertinent substrate than methanol (or other methyl compounds) in marine sediments [13CH4 values and associated carbon isotope fractionations, which might be overprinted by such mixotrophic methanogenesis. Thus, the CO2 reduction to methane and assimilation into biomass by obligate methylotrophic methanogens plays a much more important role in the environment than was previously known.But beyond known pathways, we detected an unexpectedly high amount of methane (>10%) formed from DIC. Especially in SRZ incubations, the lower methane production rates resulted in increased COediments , 7, and Supplementary materials


ACSBG2 (muscular lipid utilisation), ASBT , CLEC2B , HMGCS2 , and SCARB1  as potential mediators driving FE. Results indicate that improvements in FE exploit shifts in resource allocation which might occur at the expense of general immune responsiveness in high efficient male chickens. Consequently, to further improve FE traits and to explore causative molecular patterns, effects originating from sex-dimorphism in chickens need to be taken into consideration.Considerable variation in feed efficiency (FE) has been observed in indigenous and selected meat-type chicken populations. Although this variation could be partially linked to extrinsic factors like diet, housing environment and microbiota, it further illustrates the existence of strong molecular mechanisms enabling the differential allocation of resources for various physiological processes. To further deepen the molecular basis of individual allocation capacity in male and female broilers, an RNA-seq experiment was conducted which based on a phenotyped chicken population divergent in FE. Transcriptional differences linked to FE were pronounced in intestinal and muscular tissue sites of male animals. Specifically, signalling pathways of farnesoid X receptor (FXR) and retinoid X receptor (RXR) might contribute to mediate individual FE. The transcriptional profiles suggested  The bird’s capability for an efficient utilization of nutrients culminates in the individual’s feed efficiency (FE) which can be expressed in different ways in broilers. Most common measurements such as feed conversion ratio (FCR) and residual feed intake (RFI) consider records of energy consumption like feed intake (FI) and performance measures such as body weight gain (BWG). These proxies contribute to describe the complex molecular basis of FE traits2. Therefore, several genetic studies of FE- tested broiler populations (e.g.4) and broiler lines divergently selected for FE traits (e.g. digestive efficiency5) revealed a steadily growing number of genomic features influencing FE, FI, and BWG. Moreover, recent targeted and holistic transcriptomic analyses provide first insights into pathways and biological functions contributing to individual differences in FE of meat-type chickens. At the same time, these studies are indicative for the tissue-specific plasticity of expression patterns induced during different developmental stages (e.g.7) and under varying environmental conditions8. The mitochondrial efficiency of energy production has been identified as one of the major molecular mechanisms driving FE in muscle tissue of meat-type chickens9. In this context, AMP-activated protein kinase (AMPK) was suggested to play a considerable role via sensing the cellular energy status and balance metabolic activities11. Other main processes which were found to be affected comprise genes involved in the function and structure of the digestive system5, in the regulation of appetite as well as in lipid metabolism and transport12. Moreover, shifts in the utilization of distinct metabolic pathways, such as the shift from purine biosynthesis pathway to the purine salvage pathway were recently suggested as energy-saving strategies to improve FE13. Thus, organismal resource allocation is considered to be of central relevance to improve FE. In this respect, the energy demand that is required by the immune system was reported to be equal to 9% of the nutrient consumption14. Especially, the innate immunity is an energetically expensive process which is supposed to be suppressed in meat-type chickens selected for high growth rates15. Indeed, selection for high production efficiency might co-evolve behavioral, physiological, and immunological concerns as reviewed elsewhere16.An efficient conversion of nutrients into live weight is an important aspect of livestock production to reduce the environmental footprint and to increase the overall performance towards a sustainable intensification of agri-food productionet al.17 Building upon the study of Metzler-Zebeli et al. (2016), extreme male and female chickens with regards to RFI were selected here and analysed via RNA-seq to identify tissue-specific transcriptional responses. Thus, genome-wide transcriptome profiling comprised muscle tissue  as the major consumers of energy and different parts of the small intestine  facilitating digestion and absorption of nutrients.Despite long-term efforts to improve phenotypic traits in chickens, even individuals within highly selected broiler lines still vary considerably in their FE, nitrogen excretion and growth performance under controlled environmental conditions, as previously shown by Metzler-Zebeli The study investigates transcriptional patterns of muscular and intestinal tissues in meat-type chickens considerably divergent in their RFI. With regard to the widely unclear molecular mechanisms driving FE and the pronounced sex dimorphism in chickens, the objectives of this study were to identify sex-specific metabolic routes and molecular features contributing to FE.18. In Table The analyses of all sampled chickens with divergent RFI (n = 36) revealed differences in mean RFI values for both males  and females PENK was significantly higher abundant in breast muscle of high FE animals. In contrast, the acyl-CoA synthetase bubblegum family member 2 encoding gene ACSBG2 and a novel gene named ENSGALG00000033498 were found to be differentially abundant in males and females. Overlapping results were also present for the transcript abundance of KCNK17 (potassium two pore domain channel subfamily K member 17) and ENSGALG00000045251 in duodenal samples. For the jejunum, genes related to metabolic pathways i.e. 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3), glucose-6-phosphatase catalytic subunit (G6PC), apical sodium-dependent bile salt transporter D (ASBT/SLC10A2) and solute carrier family 10 member 2 (SLC10A2) were revealed as significantly differentially abundant in male and female chickens with opposite expression patterns in both sexes. Interestingly, the transcript encoded by the novel gene ENSGALG00000033116 was consistently less abundant in all examined intestinal parts of high FE male broilers compared to low FE male chickens. Based on the annotation of the human orthologue, this gene is predicted to encode a C-type lectin.RNA sequencing yielded an average of 80 million single reads for each sample. The subsequent mapping of reads against the chicken reference genome resulted in a concordant pair alignment rate of 87.6 ± 1.8%. The following statements refer to 44 out of 48 samples that met the quality control criteria. Considering the significance threshold (p < 0.001 and q < 0.25) the following number of genes were found to be differentially abundant between high and low FE groups: 67  and 81  in breast muscle; 60  and 59  in duodenum; 87  and 90  in jejunum; 11  and 11  in ileum , ENSGALG00000033498  and ST6GALNAC1 . Highest negative FC (high FE < low FE) were identified for ENSGALG00000019325 , AMY2A  and ENSGALG00000019845 .For genes found to be more abundant in high FE compared to low FE birds, indicated by positive fold changes (FC), highest FC differences were assigned to 10[FDR] = 23.3) and ‘LXR/RXR activation’ (−log10[FDR] = 21.1). These pathways are assigned to the ‘nuclear receptor signalling’ pathway category, which is further represented by ‘PXR/RXR activation’ and ‘LPS/IL-1 mediated inhibition of RXR function’ among the significantly enriched pathways in muscle tissue. The same canonical pathways, assigned to the ‘nuclear receptor signalling’ category, were revealed in the comparison of jejunum samples of high and low FE male chickens.The integration of RNA-seq results revealed significantly enriched canonical pathways (adjusted p < 0.05), which are presented in Table The analyses of breast muscle further indicated an enrichment of pathways assigned to the cellular immune response such as ‘acute phase response signalling’ and ‘IL-12 signalling and production in macrophages’ in male chickens. In the duodenum, the ‘superpathway of cholesterol biosynthesis’ was revealed to be altered between high and low FE animals in both sexes. In the ileum, affected pathways in males were based on orthologues genes of the human leukocyte antigen (HLA) system and were assigned to the ‘cellular immune response’ category .Biofunctions retrieved from IPA were analysed to deduce consequences as well as tissue- and sex-specific contributions in the context of FE. Biofunctions which were predicted to be significantly activated (z-score > +2) or inactivated (z-score < −2) in high FE chickens are shown in Table NR0B2 and the scavenger receptor class b member 1 encoded by SCARB1. The former was less abundant and the latter was higher abundant in high FE males compared to low FE males.In jejunum samples of FE-divergent male chickens, analysis revealed a predicted activation of molecular themes related to carbohydrate and lipid metabolism as well as endocrine system development. Specifically, IPA results predict a higher quantity of monosaccharides and a higher concentration of lipids in jejunal samples of high FE chickens compared to low FE chickens. Central molecules which contributed to all biofunctions were an orphan member of the nuclear receptor superfamily encoded by The validity of the RNA sequencing experiment and subsequent statistical data analysis was verified by comparing results obtained via RNA-seq and qPCR Fig. . The mag18. Similarly, sex-specific differences were observed for various production traits across different meat-type chicken lines20. In the studied population, the range of RFI values was higher in males than in females18. Accordingly, the subset of birds with most extreme phenotypes regarding RFI used for transcriptome analyses showed significant differences of RFI values between low FE males and low FE females. Transcriptomic profiles observed for the analysed tissues of high and low FE chickens differed considerably between the two sexes. It is also worth mentioning that a lower number of differentially abundant transcripts were identified in ileum samples compared to the other tissues analysed. This might represent the major importance of the proximal parts of the small intestine for the FE of pigs in concentrate-based diet. These sex and tissue-specific peculiarities were also reflected in the number of significantly affected canonical pathways and biofunctions in the comparisons between the different groups. Hence, despite extensive performance testing and novel insights into quantitative genetics contributing to improved FE, results implicate that certain sex-specific molecular routes and biofunctions might be targeted in the context of FE in broilers.In the context of divergent RFI as an indicator for FE, the study revealed pronounced differences between male and female broilers at the phenotypic and transcriptional level. According to the data of the whole trial population, the phenotypic differences comprised a higher final body weight, a better FCR and higher daily dry matter excretion of males compared to females21. Signalling pathways downstream of these receptors influence different developmental and metabolic processes including cholesterol and bile acid homeostasis22, which might contribute to improve FE in broilers. Indeed, an altered lipid, cholesterol and bile acid metabolism including effects mediated via FXR/RXR signalling were previously presented as one of the key molecular mechanisms driving differences of FE in the duodenum of male meat-type chickens divergently selected for RFI12. Similar pathways were found to be affected at the level of the muscle and jejunum in the current study. Based on the altered biofunctions in muscle tissue, these differences were suggested to result in the decrease of molecular transport processes and fatty acid metabolism in high FE male chickens. In this context, the ACSBG2 encoded acyl-CoA synthetase plays an important role for the regulation of lipid metabolism in chickens by initiating the intracellular decomposition or conversion of long-chain fatty acids (mainly C18:1 and C18:2)23. Although expression of human and murine ACSBG2 was reported to be specific for testis and brainstem24, the gene appeared to be among the highest expressed genes in chicken muscle of both sexes , farnesoid X receptor (FXR or NR1H4) and liver X receptor (LXR) activation. These receptors are present in numerous tissues with highest expression levels of FXR and LXR in liver, intestine and kidneySCARB1 and ASBT were found to be more abundant in the jejunum of high FE male birds, while NR0B2, which mediates the FXR effects26 was less abundant. SCARB1 encodes a plasma membrane receptor for lipoproteins which is involved in the absorption of cholesterol from the diet and, thus, is known to differ in abundance depending on the dietary level of lipids in humans28. ASBT is the primary intestinal bile salt transporter in the intestine29 and is negatively regulated by FXR26. Interestingly, the analyses of jejunal samples of female broilers revealed that ASBT was significantly less abundant in high FE animals. This might implicate sex-specific differences regarding the jejunal bile acid metabolism. Based on these results, it is suggested that high FE male chickens had an increased absorption of dietary cholesterol and a more efficient recovery of bile acid compared to low FE broilers. Moreover, it is known that an intestinal FXR activation is linked to a reduced de novo synthesis of fatty acids in other tissues30, which is in line with the predicted inactivation of fatty acid synthesis in muscle tissue of high FE male broilers.In the jejunum of male broilers, pathways dedicated to nuclear receptor signalling  seem to mediate effects on the intestinal absorption of bile salts as well as dietary cholesterol and triglycerides. Specifically, genes like G6PC, HMGCS2) and jejunum  of male chickens affect metabolic routes of carbohydrate metabolism. Specifically, effects observed in the muscle of male broilers indicate a reduced ketogenesis in high FE animals which were likely mediated via mitochondrial HMG-CoA synthase (encoded by HMGCS2), as a central regulator of ketogenesis31. This might imply for a metabolic demand to allocate sufficient amounts of carbohydrates into muscle tissue of high FE broilers. Biofunctions pointing to an increased availability of monosaccharides and lipids in the jejunum derived by a lower jejunal abundance of HMGCS2 in high FE males support this suggestion. Interestingly, chickens selected for reduced RFI values showed an increased abundance of HGMCS2 in the duodenum12. The same transcriptional alterations were found in the comparison of duodenal samples between high and low FE chickens in the current study, albeit reaching significance exclusively in females. In conclusion, the findings promote a central role of nuclear receptor signalling for FE in different tissues affecting the utilization of lipids and carbohydrates.At the same time, altered transcript abundances in muscle  was consistently found to be lower abundant in all three analysed parts of the small intestine of high FE chickens, albeit reaching statistical significance exclusively for the comparison of male broilers. In humans, CLEC2B is located in the natural killer (NK) cell gene complex and is known to encode a cell activation antigen presented by NK cells, which are an important component of the innate immune system40. Hence, the intestinal lower abundance of CLEC2B in high FE chickens might represent an indicator for a reduced activation of the innate immune system. However, due to the complex contributions to differences in FE, other aspects like FE-related differences in the intestinal microbiota composition41 need to be considered modulating the host’s immune capacity at the transcriptional level (e.g.42).Although considerable differences were observed between high and low FE chickens of both sexes, there were no signs for major differences in muscle development and cellular energy homeostasis at the transcriptional level. Especially, mitochondrial efficiency and AMPK signalling were recently proposed as important biological processes involved in improving FEPhenotype differences in RFI values were reflected by pronounced sex-dimorphic transcriptional patterns. Indeed, the RNA-seq analyses of muscle and intestine tissues in broiler chickens selected for divergent RFI revealed cholesterol and bile acid metabolism as well as immunomodulatory aspects as molecular drivers of FE in male chickens. Moreover, results indicate that improvements of FE exploit shifts in resource allocation which might occur at the expense of general immune responsiveness in high efficient male chickens. Hence, data suggest that breeding strategies have also to focus beyond improvements in FE traits towards maintenance of phenotypes balancing weight, performance and immune competence.18. In brief, one-day-old Cobb500FF birds  were housed in groups of four birds for 7 days. Afterwards, they were individually penned in cages until the end of the experimental period. Chickens were checked daily for health status and welfare issues; signs of illness led to the exclusion of animals for further analysis. Common diets based on corn and soybean meal were fed during starter (days 1–10), grower (days 11–21), and finisher periods (days 22–42) as previously described18. Ad libitum access to fresh water was provided. Individual FI was recorded daily. Body weight of all chickens was recorded weekly . To calculate overall RFI values, body weight was further measured at d 36. For RFI calculation, data for net total FI, metabolic mid-weight and total BWG between day 7 and 36 were analysed using a nonlinear mixed model  as previously described18. Accordingly, for each batch and sex, the 3 chickens with the lowest RFI (high FE) and the 3 chickens with the highest RFI (low FE), were selected at day 36 of life. Per batch, twelve RFI-divergent animals  were dissected on four consecutive days. In total, 36 birds were sampled. Gut tissue samples (1 cm2) were collected from duodenum, jejunum and ileum. Duodenum samples were taken distal to the Flexura duodeni. The jejunum was sampled at the distal end close (5 cm) to the Meckel’s diverticulum. Ileum samples were taken approximately 17 cm proximal to the ileo-caecal junction. Muscle samples  were collected from the bottom half of the left breast. Gut and breast muscle samples were immediately cleaned in phosphate-buffered saline, blotted dry on paper towel, in case of the muscle samples cut into small cubes, snap-frozen in liquid nitrogen, and stored at −80 °C until use.The conducted chicken trial was approved by the animal ethics committees of the University of Veterinary Medicine  and the national authority according to paragraph 26 of Law for Animal Experiments, Tierversuchsgesetz 2012 (GZ 68.205/0131-II/3b/2013). Animal trials were performed in three independent batches with at least 52 birds per batch. Chickens were obtained from commercial hatcheries. The experimental design was balanced for sex and comprised 157 birds . Housing and feeding conditions have been previously describedn = 12). A balanced design accounting for sex and slaughter day was applied. Descriptive statistics for all chickens were previously provided by Metzler-Zebeli et al.18. For selected animals, individual FE measurements (RFI and FCR) were compared using a linear mixed model . The model included the interaction of sex  and RFI group  as fixed effect and the day of slaughter as random effect. P-values were adjusted for multiple comparisons using the Tukey-Kramer procedure .A subset of animals divergent in RFI values  and representative for the trial population was selected for transcriptome analysis , jejunum (n = 12), ileum (n = 12), and breast muscle (n = 12) were used for RNA isolation. Extraction of total RNA was performed according to TRIzol Reagent protocol . Therefore, samples were disrupted using either mortar and pestle  or a Precellys cell disruption device . Subsequently, total RNA was treated with Baseline-ZERO DNase . Purification of RNA was achieved using the NucleoSpin RNAII kit  according to manufacturer’s protocols. Total RNA was checked on agarose gel and measured by NanoDrop ND-1000 . The quality of RNA was assessed employing an Agilent 2100 Bioanalyzer . All samples had RNA integrity numbers (RIN) values ≥ 7.8. Subsequent extraction of mRNA was supported by a magnetic mRNA Isolation Kit . Libraries were prepared using the TruSeq Stranded mRNA preparation kit . Quantity of libraries were analysed using both a DNA 1000 chip on a Bioanalyzer instrument and the Illumina Library Quantification Kit  performed on a LightCycler 480 PCR System . Quality controlled libraries were sequenced on an Illumina HiSeq. 2500 instrument (Illumina) by generating 125-bp paired-end reads in high-output run mode as described by the manufacturer.After DNA extraction following a conventional phenol/chloroform procedure, the sex of selected animals was verified by PCR using primers specific for chicken sex chromosome WGallus gallus genome build 5, March 2017). Read counts per gene were calculated via htseq-count version 0.6.1p144. In order to exclude genes with very low read counts, features with less than 5 reads in at least 2 samples were discarded from further analyses. Quality of sequencing data was assessed using the arrayQualityMetrics package for R (version 3.32.0). The package uses three different outlier detection approaches, including the distance between individual data sets, the distribution of signal intensities and the quality of the individual data set. Samples were judged as outliers which were conspicuous in at least two of these criteria. In total, 4 out of 48 samples  were removed from further analyses  and Bowtie (version 1.1.1.0) mapping tools were used to align the sequences to the chicken reference genome  were calculated using the qvalue R package following the Benjamini-Hochberg (BH) procedure (version 2.8.0). The significance threshold was set at p < 0.001 and q < 0.25. Fold changes were calculated to display the relative transcript abundance between high FE and low FE groups . No FC cut off was applied. The number of differentially abundant transcripts and the size of the intersections between experimentally groups were displayed using the UpSetR package46.Analysis of differentially expressed genes was performed using the DESeq. 2 package of the R environment47.Lists of significantly altered transcripts were evaluated with Ingenuity Pathway Analysis . Human gene identifiers were preferentially used if available. Therefore, orthologous gene identifiers were assigned using the BiomaRt R package . Results related to canonical pathways and biofunctions were considered significant at a Benjamini-Hochberg adjusted p-value < 0.05. In addition, molecular themes related to biofunctions had to pass a second cut-off criteria  stating a prediction of its activation statusACSBG2, AMY2A, AQP4, CA7, FABP4, FNDC5, G6PC, GATM, GBP, HPX, PFKFB, THRSP) and reference genes  were quantified by qPCR using transcript-specific primers. Primer specifications and tissues analysed are shown in Supplementary Table 7–102 copies). Values were calculated by factorial normalisation on ACTB, GAPDH, and DCAF7 expression values. Correlation of normalized expression values was calculated using Pearson test and considered significant at p < 0.05.First-strand cDNA was synthesized from 1.5 µg of total RNA using random primers and oligo d(T) 13VN in the presence of Superscript III reverse transcriptase  and RNAsinPlus RNase Inhibitor . The cDNA samples were diluted in 200 µL Aqua dest. and stored at −20 °C until further analyses. Transcript levels of selected target (Table S1Table S2, Table S3, Figure S1


The enzymes GALNTs add GalNAc sugar to Ser and Thr residues, forming the Tn glycan. GALNTs are activated by trafficking from Golgi to ER, a process driven by the Src kinase and negatively regulated by ERK8. This GALNTs activation (aka GALA) pathway induces high Tn levels and is a key driver of liver tumor growth. Recently, Tabak and colleagues have contested our previous data that EGF stimulation can induce GALNTs relocation. Here, we show that relocation induced by EGF is actually detectable in the very images acquired by Tabak et al. Furthermore, we show that over-expression of EGFR strongly enhances EGF-induced relocation and that EGFR appears required to drive relocation induced by ERK8 depletion. Direct co-localisation of GALNT with the ER marker Calnexin is observed after EGF stimulation. We furthermore propose that quantification of O-glycosylation of the ER resident protein PDIA4 provides a mean to quantify GALA independently of imaging. In sum, we demonstrate that the claimed non-reproducibility was due to experimental imaging conditions, that EGFR is indeed a driver of GALA and propose additional markers to facilitate the study of this pathway. Replicability is essential to the scientific progress and has been the subject of intense debate in recent years. In biomedical sciences, some authors have argued that a large fraction of scientific studies are unreproducible, calling into question the value of discoveries and initiating a fierce debate –3.In a study first posted on BioRxiv and later published, Tabak and colleagues questioned the replicability of findings we published in 2010 and the physiological relevance of the GALNTs Activation (GALA) pathway. In the O-GalNAc glycosylation occurs on thousands of secreted and cell surface proteins and is essential for multicellular life –8. O-glyThe formation of Tn has received a lot of attention from glycobiologists because malignant tumors have long been reported to have dramatically increased levels of Tn , 12. TheIn our 2010 paper, we proposed that an alternative mechanism can also drive high Tn: the relocation of GALNTs to the ER induces an accumulation of Tn in this organelle. Since the ER is a large organelle and tends to mesh the whole cytoplasm, the result is an increase of total cellular staining detectable by lectin-based histochemistry . ImportaIn a subsequent study, using VVL staining fluorescence imaging and quantitative analysis on tissue microarrays, we evaluated Tn levels increase to be up to 10 to 15 folds in human breast cancer tissues . We showHow is the relocation process controlled? An RNAi screening approach revealed that GALNTs relocation is under the control of a complex genetic network. Upon depletion of a number of genes, Tn cellular staining significantly increases. 12 different genes were validated . In the In their study, Tabak and colleagues used EGF and PDGF stimulation with GALNTs and organelle markers staining followed by serial confocal imaging. They reported that they could not observe a decrease GALNTs colocalisation with a Golgi marker or increase of colocalisation with an ER marker.in vitro and in vivo.In the intervening months, we have been able to analyse the raw data acquired by Herbomel et al and shared during publishing. We have repeated experiments and extended the study of EGF stimulation. We found that, albeit moderate, the relocation was present in the images acquired by Herbomel but could not be quantified by the analytical method they chose. We further confirmed that EGF and PDGF stimulation does induce changes in the pattern of Tn and GALNT staining. We observed that these experiments are sensitive to culture conditions, in particular to FBS source. Finally, we show that EGFR expression enhances relocation and present a new marker to facilitate the modeling and measurement of the GALA relocation process While we were analysing the causes of discrepancy between our results and those of Tabak’s group, we considered the possible influence of cell lines and culture conditions. HeLa cell lines are known to be highly variable . HoweverAs most investigators, we grow HeLa cells with 10% Fetal Bovine Serum (FBS) which contains various growth factors and cytokines. Before growth factor stimulation, cells were washed twice with PBS before overnight starvation in serum-free media. Over the years, we observed that different batches of FBS can have an effect on basal levels of Tn. We tested whether, despite the washing step, two different batches of FBS could affect the experiment. With one batch of FBS (FBS1), we were able to observe an increase of 1.5 to 2 fold in Tn levels after 6h of EGF stimulation and to a lower extent with PDGF treatment . HoweverWe next repeated the same experiment to measure the levels of total phosphotyrosine and Src activation after EGF stimulation. Consistent with the results with GALA, we observed that FBS1 induced a marked activation of Src, while FBS2 had a very limited effect . In theiHerbomel et al. used confocal imaging at high magnification with extensive sectioning (61 slices). As previously noted in our commentary of their study, this extensive sectioning can have two effects detrimental for detection of GALNTs relocation: it prevents the visualisation of weak signal and is prone to bleaching the weak signal originating from the ER . Dr. TabWe next wondered why the image quantification protocol used did not detect any change. We realised that the analytical method chosen was inadequate to quantify relocation for two reasons. The first is the use of an auto-thresholding (by a method known as “Costes”) instead of using a fixed threshold. In conditions where a signal such as GALNTs is transferred from a very concentrated location (the Golgi) to a very “dispersed” location (the ER) with low signal levels, auto-thresholding results in the low signal being partially or completely excluded from the analysis. This issue has been identified multiple times in our group and reported by others . In ordeWe used Herbomel’s images to re-run the Manders coefficient analysis and found that indeed M2 did not register any effect; but the M1 coefficient showed a significant decrease. To facilitate comparisons, we normalised M1 and M2 to the control at 0h as the relative changes upon EGF stimulation . We alsoWe could not perform the same analysis on all the images provided by Tabak’s group as some of them display inconsistent total intensity levels, suggesting that acquisition parameters were not kept constant. There is overall lower intensities in images of EGF stimulated cells. This is readily apparent in the staining of ER marker calnexin (CANX), whose levels should not change upon EGF treatment . Given tOne of the key concerns of Tabak and group was the alleged lack of colocalisation of GALNT with an ER marker after EGF stimulation. As shown in We conclude that the lack of effect reported by Herbomel et al. is due to their image analysis methods and acquisition settings.EGF stimulation effect on the intracellular distribution of GALNTs requires optimal conditions of imaging. In many cases, endogenous GALNTs staining in the ER is weak and difficult to detect . This isWe previously reported that ERK8 depletion induces the redistribution of GALNTs to the ER, quantified via measurement of colocalization with the ER marker Calreticulin . Here, wOur previous results collectively indicate that EGFR is a regulator of GALA. But levels of expression of this receptor are known to vary extensively; this could explain why EGF stimulation is sometimes not very effective. We thus transfected HeLa cells with EGFR, then stimulated them with EGF. This led to a marked increase in Tn levels of more than 6 fold on average . The effTo better visualize ER relocation of GALNT upon growth factor stimulation, we stimulated EGFR transfected cells that stably expresses exogenous GALNT2-GFP. While the GALNT2-GFP remains predominantly in the Golgi in unstimulated cells, there is clear redistribution of GALNT2-GFP that colocalised with ER marker CANX after 4 hours of EGF stimulation . In thesWe previously reported that growth factor stimulation leads to displacement of ERK8 from Golgi membranes . Here, wWe finally tested how general is ERK8 negative regulation of GALA, we repeated the knockdown in two other cell lines. SKOV3 is a cell line originating from an ovarian cancer, with epithelial characteristics. ERK8 depletion led to an 8-fold increase in Tn levels in these cells . HoweverHPL and VVL staining have been associated with structures alternative to Tn. A concern of Dr. Tabak during our exchange of emails was that we were using HPL or VVL staining instead of relying only on GALNTs. We thus performed a double knock-down of GALNT1 and 2, the main GALNTs expressed in Hela cells. DepletiAs reported in 2010, GALNT staining reveals punctate structures at the periphery of the Golgi a few hours after EGF stimulation . These sAs discussed above, microscopy imaging to quantify GALA can present certain technical limitations. However, the relocation of GALNTs to the ER also induces measurable biochemical changes. We recently identified PDIA4 as a resident ER protein that gets hyperglycosylated upon GALA activation. PDIA4 is hyperglycosylated in tumors that show increased levels of Tn .When Hela cells were stimulated with EGF, we found that PDIA4 glycosylation increased by 2.5-fold. After transient over-expression of EGFR and stimulation by EGF, it was stimulated by nearly 4-fold . We alsoFactors influencing the reproducibility of molecular biological studies are unfortunately varied and numerous. Even cell lines in culture are complex and variable systems with genetic drift and components poorly defined such as FBS. In this study, we have sought to understand why Tabak and colleagues claim that they were not able to reproduce our findings published in 2010. We identified two answers. One is linked to a potential source of variability in these experiments: FBS batches. We found that the batch of FBS used to grow cells can significantly affect GALA response. Effects of FBS batch on signaling are well documented and unfortunately hard to control . HerbomeThe second answer is less hypothetical: Herbomel et al. did in fact obtain relocation of the GALNTs in their experiments. Using the original raw images shared by them, we found that by changing the display method, the dispersion of GALNTs becomes clearly visible. Furthermore, we found that the image analysis protocol they followed would never have allowed detection of the relocation. Adjusting this protocol with the correct parameters, we were able to quantify GALA effect on GALNT1, GALNT2 and Tn staining in the images they acquired.Of note, GALA is not an on/off system, but rather a rheostat-type regulatory process. This is in contrast with other signaling events such as activation of ERK1/2, which tends to function rather as an on/off switch. In cells stimulated by growth factors, GALA activation can be relatively moderate, especially in contrast with the situation in tumor cells in situ. GALA levels tend to correlate with the levels of activation of tyrosine kinases as evaluated by phospho-tyrosine levels. Src (or related tyrosine kinases) activation after EGF stimulation tends to be weaker than ERK1/2 (see for instance ). GALA rAn active form of Src strongly induces the GALNTs relocation process, an observation that could be reproduced by Tabak’s group (e-mail communication). A complication here is that too strong or too long a Src activation can also lead to Golgi fragmentation, especially in HeLa and other epithelial derived cell lines, as previously reported . This cain vivo? This is not clear at this stage. High levels of EGFR expression and activity are known to be associated with many different tumors, including breast [By comparison with the growth factor stimulation experiment, our data indicate that GALA is more strongly activated in most human breast and liver tumors. Obviously, this is the relevant context in which to consider this pathway. Are growth factors important g breast  and liveg breast ; so thisg breast . In fineIn a world increasingly concerned with scientific reproducibility, it is equally important to recognize the challenges when attempting reproduction . The com2 incubator.Hela cells were obtained from ATCC. Skov-3 cells were a gift from E. Chapeau. Both Hela and Skov-3 cells were grown in DMEM supplemented with 10% fetal bovine serum (FBS). HEK293T cells were a gift from W. Hong  and were grown in DMEM supplemented with 15% FBS. All cells were grown at 37°C in a 10% COHelix pomatia Lectin A (HPL) conjugated with 647-nm fluorophore (#L32454) and anti-GFP (#A11122) were purchased from Thermo Fisher Scientific. Anti-Giantin (#ab24586), anti-actin (#ab8227), anti-PDIA4 (#ab155800) antibodies were purchased from Abcam. Anti-pY416-Src (#2101), anti-Src (#2109), anti-pY-ERK1/2 (#4377), anti-ERK1/2 (#4695) antibodies were purchased from Cell Signaling Technology, Inc. Biotinylated Vicia Villosa Lectin  and agarose bound VVL (#AL-1233) were purchased from Vector Laboratories, Inc. Anti-phosphotyrosine clone PY20 (#05–947) and anti-phosphotyrosine clone 4G10 (#05–321) were purchased from Merck Millipore. Fetal bovine serum  were purchased from Thermo Fisher Scientific.Recombinant human epidermal growth factor EGF (#SRP3027) was purchased from Sigma aldrich. PDGF-BB Recombinant Human Protein (#PHG0046), Mouse anti-GALNT1 antibody in hybridoma supernatant was a gift from H. Clausen . GFP tagged epidermal growth factor receptor (EGFR) was a gift from W. Hong. siRNAs were purchased from Dharmacon, Inc.EGFR inhibitor AG-1478 (#S2728) was purchased from Selleckchem. Src family kinase inhibitor PP2 (#529573) was purchased from Merck Millipore.Plasmid transfection in Hela cells and HEK293T cells were performed with Fugene HD (Promega) and Lipofectamine 3000 (Thermo Fisher Scientific) respectively. Cells were transfected for at least 24 hours before further manipulations. siRNA transfection was described in detail in . BrieflyFor growth factor stimulation, cells were washed twice using Dulbecco’s phosphate-buffered saline (D-PBS) before overnight serum starvation in serum-free DMEM. Human recombinant EGF  or mouse recombinant PDGF-bb  were added for various durations before fixation with paraformaldehyde or lysed with RIPA lysis buffer.For drug treatments, drugs were prepared by reconstituting in DMSO in concentrated stock solutions. The drugs or DMSO control were diluted in media containing 10% FBS and added to cells for 6 hours (AG-1478) or 24 hours (PP2) before fixation.2 before growth factor stimulation or plasmid transfection. IF staining procedures was performed as reported in [For automated imaging, Hela cells were seeded in a 96-well clear and flat-bottomed black imaging plate  and incubated overnight at 37°C and 10% COorted in , 20. CelFor high resolution microscopy, cells were seeded onto glass coverslips in 24-well dishes . The procedures for IF staining were the same as described above. To observe phosphotyrosine staining, the cells were permeabilized with 0.2% Triton-X for 2 hour at room temperature and stained with anti-phosphotyrosine clone PY20 antibody diluted in 2% FBS in D-PBS overnight. Cells were mounted onto glass slides using FluorSave (Merck) and imaged with immersol oil using an inverted confocal microscope (Zeiss LSM800) at 40X, 60X or 100X magnification.Image analysis of HPL intensity of images acquired on IXM was performed using MetaXpress software (version 5.3.0.5). For each well, total HPL staining intensity and nuclei number was quantified using the ‘Transfluor HT’ application module in the software. Hundreds of cells from at least three wells per experiment were quantified. Two experimental replicates was performed.Image analysis of phosphotyrosine levels at the Golgi were quantified using the ‘Translocation-enhanced’ application module in the software whereby the intensity of PY20 staining within the Golgi area (demarcated by Giantin staining) per cell was quantified. Hundreds of cells from at least three wells per experiment were quantified. Two experimental replicates was performed.For ImageJ analysis of HPL intensities, images were exported as 16-bit TIFF files. A fixed threshold for a mask on the HPL channel was set and the total intensity per image was calculated based on the total pixel count multiplied by the intensity per pixel. The HPL intensity per cell was then obtained by normalising the total image intensity with the nuclei count.For analysis of Mander’s coefficient, the images were analysed with ImageJ plugin . A fixed threshold to distinguish from background signal was set on both HPL/GALNT and Golgi channels for all images and the corresponding fraction of HPL/GALNT coincident with Golgi channel (“M1”) and fraction of Golgi coincident with HPL/GALNT (“M2”) was then used to quantify the colocalization between the markers.Tabak’s group provided one representative image stack from each experimental condition in .nd2 file format. Each image stack comprise of a z-stack of 61 images for each channel. Each image contains 3–4 cells acquired at 60x magnification. To analyse images provided by Tabak’s group, an ImageJ plugin (Nikon ND2 Reader) was used to export z-stacks of each channel in .avi format and the maximum projection was generated from each z-stack. All images were exported under the exact same settings. The Mander’s coefficient was analysed with JACOP using the z-stacks from different channels whereby a fixed threshold was set for each of the two channels in the set of images within the same experiment. The maximum projection of the z-stack was presented in the figures.To remove Golgi localized GALNT signal with ImageJ, the maximum projection image of Golgi marker TGN46 was first generated as a binary mask. Any GALNT signal within this Golgi mask was subtracted and removed, generating an image with only GALNT signal outside the Golgi, Each cell was cropped to obtain individual cellular data and JACOP was used to quantify Mander’s coefficient with ER marker CANX.Image analysis of phosphotyrosine levels at the Golgi were quantified using the ‘Translocation-enhanced’ application module in the software whereby the intensity of PY20 staining within the Golgi area (demarcated by Giantin staining) per cell was quantified.For object-based colocalization analysis of ERGIC53 and GALNT1 punctate structures, a fixed threshold for each of the channels was set to distinguish discrete objects and from background noise. The intensity centres of each discrete objects i.e. centroids of each channel was calculated in the ImageJ plugin (JACOP). Two objects were considered to colocalise if the distance between their centroids was less than the resolution of the microscope used and the percentage of the objects in the ERGIC53 channel colocalizing with objects in the GALNT1 channel was calculated for each cell.Cells were washed twice with ice-cold D-PBS before lysis with RIPA lysis buffer containing protease and phosphatase inhibitor (Roche). The protein concentrations of clarified cell/ tissue lysates were measured using the Bradford reagent (Bio-Rad) and normalised across samples. At least 1mg of total lysate was incubated with VVL-conjugated beads for overnight at 4°C. The beads were washed at least three times with RIPA lysis buffer, before the precipitated proteins were eluted in 2x LDS sample buffer with 50mM DTT by boiling at 95°C for 10 minutes. The samples were resolved by SDS-PAGE electrophoresis using bis-tris NuPage gels as per the manufacturer’s instructions (Thermo Fisher Scientific) and transferred to nitrocellulose membranes. Membranes were then blocked using 3% BSA dissolved in Tris buffered saline with tween  for 2 hours at room temperature before incubation with lectin or antibodies overnight. Membranes were washed at least three times with TBST before incubation with secondary HRP-conjugated antibodies . Membranes were further washed at least three with TBST before ECL  exposure.S1 Fig(A) HPL staining of cells stimulated with EGF over the indicated durations performed in Bard’s lab. The Golgi is demarcated by MannII-GFP. Scale bar: 30 μm. (B) Mander’s coefficient to quantify the level of colocalization between HPL and Golgi marker MannII-GFP over time of EGF stimulation in (A). M1 represents the fraction of HPL staining overlapping the Golgi and M2 represents the fraction of Golgi overlapping HPL staining. Values were normalised with respect to unstimulated control cells (0 h). Hundreds of cells were quantified. Statistical significance (p) measured by two-tailed paired t test. **, p < 0.001 relative to unstimulated cells (0 h). (C) Mander’s coefficient values of GALNT1 and Golgi marker TGN in (TIF)Click here for additional data file.S2 Fig(A) Immunoblot analysis of GALNT1 levels in Hela cells depleted with ERK8 single (“siERK8 (single)) or ERK8 pooled (“siERK8 (pooled)) siRNA. (B) More representative images of GALNT2-GFP cells expressing EGFR-mcherry with and without EGF stimulation. Scale bar: 10 μm (C) Quantification of Mander’s coefficient quantification in EGFR expressing GALNT2-GFP cells. More than 33 cells were quantified for each condition. Statistical significance (p) measured by two-tailed paired t test. *, p < 0.05, **, p < 0.01 ***and p < 0.001 relative to unstimulated cells (0 h). (D) HPL staining of ERK8 depleted Hela cells treated with DMSO control, 10 μM Src inhibitor PP2 or 10 μM Src Kinase Inhibitor I (SKI-I) for 24 hours. Scale bar: 30 μm (E) HPL staining of ERK8 depleted Hela cells (“siERK8”) treated with 10 μM EGFR inhibitor AG-1478 or DMSO control. Scale bar: 30 μm. (F) HPL staining of ERK8 depleted Skov-3 cells. Scale bar: 30 μm. (G) Quantification of HPL intensity in (F). Statistical significance (p) measured by two-tailed paired t test.*, p < 0.05 relative to siNT control.(TIF)Click here for additional data file.