TRP channels respond to a variety of chemical and physical stimuli derived from harmful agents and contribute to increased intracellular cation concentrations. TRP channel-mediated effects in immune cells are diverse and range from regulation of cell migration and phagocytosis, to the production and release of inflammatory mediators. Furthermore, these channels mediate an active crosstalk between epithelial cells, neuronal tissue, and the immune cells that orchestrate immune responses to tissue damage or infection. The articles published in this special issue review current thinking with regards to the role of TRP channels in innate immune cells, covering from the prototypical phagocytic cells, neutrophils, and macrophages, to other innate immune cells like mast cells and natural killer cells. Original articles and reviews highlight the involvement of TRP channels in regulating the inflammatory properties of innate immune cells, and how these processes shape the outcome of diseases including inflammatory bowel disease, lung disease, allergic disorders, infectious and autoimmune diseases. Because of the wide functional role of TRP channels in inflammation and immunity, authors discuss the use of specific agonists or antagonists and the potential for development of novel treatments for infectious and/or inflammatory diseases.Robledo-Avila et al. adds new knowledge to the role of TRPM2 channels in neutrophils during a L. monocytogenes infection. They show that a role of TRPM2 channels is to contain the inflammatory response to a L. monocytogenes infection. Accordingly, TRPM2−/− mice develop septic shock and TRPM2−/− neutrophils acquire a hyperinflammatory profile. The increased inflammatory properties of TRPM2−/− neutrophils correlate with dysregulated cytoplasmic concentration of Ca2+, which potentiate membrane depolarization and accounts for the higher susceptibility of TRPM2−/− mice to infection. Whereas the importance of TRPM2 in regulating the intracellular Ca2+ concentration ([Ca2+]i) in neutrophil function has been studied, TRPM2 as non-selective cation channel, is also permeable to Na+. However, the impact of this channel in modulating the intracellular Na+ concentration ([Na+]i) is unknown. The original research article by Najder et al. exams for the first time how knockdown of TRPM2 may affect the intracellular Na+ homeostasis and chemotaxis of neutrophils. The authors found that knockout of TRPM2 channel results in altered neutrophil [Na+]i, likely by indirectly modulating the Na+ transport protein NCX1. Therefore, they postulated that TRPM2 channel regulation of cation balances may be essential under inflammatory environment.In the special issue, several original papers focus on TRP channels in neutrophils. The work by Fliegert et al. critically summarize the literature regarding the role for cADPR as an agonist of TRPM2 channel, with an emphasis on recent structural data. Authors conclude from the literature that removal of contaminating ADPR prevents activation of TRPM2 by commercial cADPR, nonetheless, the idea that cADPR could affect TRPM2 channel remains unsettled.TRPM2 channel is widely expressed in immune cells and it is firmly established that the channel can be activated by intracellular adenosine 5′-diphosphoribose (ADPR). However, additional NAD derivatives including NAADP and cADPR have been considered TRPM2 agonists, but the activating mechanism and activation site of the channel for these nucleotides remain controversial. In a review article Nadolni et al. investigates the role of TRPM7 channels in neutrophil inflammatory recruitment with a particular focus on the kinase domain of this channel. They found that mice whose TRPM7 channels bear an inactive kinase domain are recruited less efficiently in a peritonitis model. This is underpinned by in vitro studies that reveal reduced chemotaxis and reactive oxygen species production in the presence of TRPM7 channel or kinase blockers.Another original research article by Michalick and Kuebler provide an overview on how the mechano-sensitivity of TRPV4 channels (“mechanoTRPV4”) impacts on their role in immune cells (“immunoTRPV4”). Scheraga et al. discus the link between mechanics and signaling in a narrower context for macrophages and lung injury. Furthermore, Alpizar et al. report in an original research that TRPV4 mediates LPS-induction of inflammatory innate immune responses in urothelial cells. TRPV4 is highly expressed in urothelial cells and is known to play a role in sensing the normal filling state of the bladder and the mechanisms of bladder voiding. The regulatory role of TRPV4 on the increase in proinflammatory cytokine expression induced by bacterial LPS is a novel finding.TRPV4, members of the vanilloid (TRPV) subfamily of TRP channels, are widely expressed mechanosensitive channels also found in many (innate) immune cells, where they contribute to their activation and differentiation. Immune cells are challenged by many mechanical cues that may originate from the blood stream during the recruitment process, from the surrounding extracellular matrix or be a consequence of the respective organ function such as ventilation or heartbeat. The new concept of mechanoimmunology attempts to bring the function of immune cells and their response to mechanical cues in a causal relationship. Two reviews are evaluating this idea with TRPV4 channels being the common denominator. Tsvilovskyy et al. nicely demonstrate that TRPC channels contribute at least partially to mast cell activation via the Mas-related G-protein coupled receptor member B2 (MrgprB2), a mast cell-specific receptor for basic secretagogues, such as the widely used compound 48/80 or substance P. On the other hand, mast cell activation following FcϵRI stimulation is not affected by TRPC channels. Authors support their claim that TPRC channels might be associated with systemic pseudo-allergic reactions by using double (Trpc1/4−/−) and triple (Trpc1/4/6−/−) knockout mouse models and a thorough comparison of bone marrow derived mast cells versus peritoneal mast cells. In the other study, Bacsa et al. elegantly test the principal possibility of pharmaco-optogenetic modulation of the function of immune cells using a recently established TRPC3/6/7 selective photochromic benzimidazole agonist OptoBI-1. The researchers demonstrated that the rat basophilic cell line, RBL-2H3, lacks noticeable Ca2+/NFAT signaling in response to OptoBI-1 photocycling. Different genetic modifications of these cells, by introduction of recombinant benzimidazole-sensitive TRPC isoforms (TRPC3/6/7), revealed that exclusively the single expression of TRPC6 generates OptoBI sensitivity suitable for opto-chemical control of NFAT1 activity. These results provide the first proof-of-concept for efficient chemo-genetic targeting of Ca2+ signaling in basophils and transcriptional regulation based on TRPC photo-pharmacology.Mast cells and basophils are essential drivers of allergic and anaphylactic reactions. Two original papers focus on the role of TRPC channels in these innate immune cell types. Spix et al. critically review the multiple functions of TRPML channels in regulating immune responses. This includes the TRPML1-mediated modulation of secretory lysosomes, granzyme B content, tuning of effector function in NK cells, TRPML1-dependent directional dendritic cell (DC) migration and DC chemotaxis, and the role of TRPML2 in chemokine release from LPS-stimulated macrophages. However, they noted that expression and the functional roles for TRPML channels on other very diverse immune cell types  remain to be elucidated. With a more specific focus on TRPML channels on NK cell functionality and cancer immunotherapy, Clement et al. provide a concise review of lysosome biogenesis in NK cells. They further highlight methodological advances and new specific pharmacological modulators generated in the last years and their potential for future studies.Unlike most TRP channels, which are expressed at the plasma membrane, endolysosomal TRP mucolipin channel family (TRPML), are found in the endolysosomal system. Endosomes and lysosomes are involved in many aspects of immune cell function, such as phagocytosis, antigen presentation and processing by antigen-presenting cells, release of proinflammatory mediators. Consequently, TRPML channels must play critical roles in inflammation and immunity. In this special issue, Santoni et al. review the impact of TRPML channels on mammalian anti-viral responses as well as on NK cell function. They highlight, on the one hand, an essential role of TRPML1 and 2 channels in the promotion of virus entry and infectivity and, on the other hand, the contribution of TRPML channels enhancing antiviral innate and possibly adaptive immune responses by regulating TLR signaling in different innate immune cells. Thus, TRPML channels might form a double-edged sword in the innate immune response to viral infections.In addition, Chen et al. review and summarize the plethora of findings linking the functions of TRP channels in immune cells as well as sensory nerves in the pathogenesis of inflammatory bowel disease. Similarly, the review by Silverman et al. elaborates further on how neuronal TRP channels drive the inflammatory processes in general. These reviews clearly highlight the significance of TRP channels in inflammatory processes, but they also reveal that there are glaring mechanistic gaps in our understanding of how TRP channels and their downstream electrical signals regulate these inflammatory processes – much work is needed to understand how TRP channels regulate intracellular signaling in immune cells and how their activities help coordinate the complex cellular networks that underly tissue inflammation.There is an emerging theme that TRP channels play a diverse yet poorly defined role in the immune– nonimmune cell crosstalk during inflammatory processes. In summary, this special issue of Frontiers in Immunology presents a comprehensive overview of the most recent data on the role of several TRP channel families in innate immunity. It highlights the importance of these proteins as potential drug targets for future therapeutics against allergic reactions, inflammatory or infectious diseases.All authors listed made direct intellectual contribution to the work, wrote, edited, and approved the final manuscript for publication.SP-S was supported by the Cystic Fibrosis Foundation grant PARTID18P0. BD was supported by NIH grants GM108989 and HL120840. AS was supported by Deutsche Forschungsgemeinschaft SCHW407/17-1 and IZKF Münster Schw2/020/18, and SZ was supported by the Deutsche Forschungsgemeinschaft (DFG) TRR-152/2 (P14).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The mechanisms of lymphedema development are not well understood, but emerging evidence highlights the crucial role the immune system plays in driving its progression. It is well known that lymphatic function deteriorates as lymphedema progresses; however, the connection between this progressive loss of function and the immune-driven changes that characterize the disease has not been well established. In this study, we assess changes in leukocyte populations in lymph nodes within the lymphatic drainage basin of the tissue injury site  using a mouse tail model of lymphedema in which a pair of draining collecting vessels are left intact. We additionally quantify lymphatic pump function using established near infrared (NIR) lymphatic imaging methods and lymph-draining nanoparticles (NPs) synthesized and employed by our team for lymphatic tissue drug delivery applications to measure lymphatic transport to and resulting NP accumulation within dLNs associated with swelling following surgery. When applied to assess the effects of the anti-inflammatory drug bestatin, which has been previously shown to be a possible treatment for lymphedema, we find lymph-draining NP accumulation within dLNs and lymphatic function to increase as lymphedema progresses, but no significant effect on leukocyte populations in dLNs or tail swelling. These results suggest that ameliorating this loss of lymphatic function is not sufficient to reverse swelling in this surgically induced disease model that better recapitulates the extent of lymphatic injury seen in human lymphedema. It also suggests that loss of lymphatic function during lymphedema may be driven by immune-mediated mechanisms coordinated in dLNs. Our work indicates that addressing both lymphatic vessel dysfunction and immune cell expansion within dLNs may be required to prevent or reverse lymphedema when partial lymphatic function is sustained. There anic acid . A previnic acid . The culPrevious reports have focused primarily on studying leukocyte infiltration into lymphedematous tissue to explain their effects on the existing lymphatic vasculature and the resultant swelling. Few studies have examined how leukocyte populations in downstream lymph nodes (LNs) respond during lymphedema. Garcia Nores et al. found that CD4+ T cells were activated by dendritic cells in regional LNs and migrated to the site of injury to initiate lymphedema . LeukocyMany previous studies of lymphedema used the mouse tail double vessel ligation model where all initial and collecting lymphatics in the tail are blocked due to circumferential ligation of lymphatics encircling the tail ,18. This4 antagonism with bestatin. Our findings demonstrate that leukocyte populations extensively expand in dLNs following lymphedema induction, and this increase in lymph node leukocyte populations is correlated with the accumulation of NPs draining the injury site within the dLNs. Additionally, we show that treatment with bestatin increases lymphatic contractile transport and NP accumulation during lymphedema progression but does not reduce the observed leukocyte expansion in the dLNs or the tail swelling response characteristic of lymphedema.This study presents a detailed analysis of time-varying changes in LN leukocyte populations during lymphedema using this single vessel ligation model. In so doing, both the immune response within the dLN in lymphedema and how flow into the LN may modulate these changes were simultaneously delineated. Moreover, we utilize this model to explore the kinetics of transport, swelling, and immune cell populations within the dLN in the context of LTBTo study how various immune cell populations in dLNs change during lymphedema progression, we used a single vessel ligation lymphedema mouse tail model developed by our group . This mop = 0.1323), while there was a negative correlation for cytotoxic T cells (p = 0.1150)  C. These Similar to the varied presentation of lymphedema clinically, the single vessel ligation lymphedema mouse tail model used in this study results in a swelling response of the tail that varies amongst animals in its severity as well as rate of progression. This allows how the extent of swelling impacts leukocyte populations in the intact dLN to be studied. The swelling observed herein showed a similar increase in tail volume as observed in previous reports, with percent volume change reaching a maximum at 3W . Using STo measure transport to and NP accumulation within dLNs, we used a nanoparticle system that has been previously shown to preferentially drain into lymphatic vessels after injection and accumulate within dLNs ,22,23,24Immune cell expansion in the intact vessel dLN was compared to that of the injured vessel dLN post injury. We found no significant differences between intact and injured vessel dLNs for any of the leukocyte populations we surveyed . Howeverrophages A. Additirophages B. This irophages B.p = 0.0307) and close to significant for normalized mean fluorescence (p = 0.0509), showing that the slopes of these NP fluorescent measurements in the intact vessel dLN versus time were different between treatment groups. However, fluorescence in the injured vessel dLN at 3W showed no difference between the bestatin and saline groups (Leukotriene B4 (LTB4) is a known chemoattractant and has been shown to play a bimodal role in lymphangiogenesis, with low concentrations being lymphangiogenic and high concentrations being anti-lymphangiogenic ,25,26. Pe groups . Additioe groups E. These Given the observed increase in lymphatic function following bestatin treatment, we were interested in studying if LTB4 mediated the observed immune cell expansion in the dLNs in the context of lymphedema. Using the flow cytometry protocol described earlier, we found that bestatin treatment had no significant effect on either number of leukocytes or frequency of leukocytes in the summed dLNs for the leukocyte subsets analyzed compared to the saline control group A,B. ThisWe also wanted to analyze how LTB4 antagonism would differentially affect immune cell expansion in the intact vessel dLN versus the injured vessel dLN. We again analyzed the LNs separately at each timepoint, comparing total cell number between the intact and injured nodes for bestatin-treated mice. For bestatin-treated mice, the intact vessel dLNs had more T and B cells, myeloid cells, dendritic cells, monocytes, and macrophages than the injured vessel dLNs at 2W . NormaliThe immune response during lymphedema development has been previously well characterized in lymphedematous tissue ,10,12,13We have additionally identified that B cells increase in number during lymphedema development in the dLNs and overtake T cells as the predominant leukocyte subset within the dLNs A,B. PrevMyeloid cells, primarily macrophages, have been suggested to play an important role in driving lymphatic failure and tissue fibrosis during lymphedema development ,4,37. OuInflammation has been previously shown to induce lymphangiogenesis within the lymph node . Our resOne major question regarding the pathogenesis of lymphedema is whether the onset of swelling is due to a loss of lymphatic function, which initiates the resulting immune response, or whether this loss of lymphatic function is a byproduct of immune-mediated physiological changes. To begin to answer this question, we combined a detailed analysis of immune cell composition in the dLNs during lymphedema development with experiments designed to track nanoparticle transport and uptake to the dLNs. Our novel single vessel ligation lymphedema model additionally allowed us to determine how differences in transport to the dLNs may impact the resultant expansion of LN resident leukocytes. We found that transport to and accumulation of NPs within the intact vessel dLN as measured by the normalized sum of fluorescence did not change significantly during lymphedema progression, while NP accumulation within the injured vessel dLN correspondingly increased B,C. ThisTo understand how anti-inflammatory treatment may affect the composition of leukocytes within the dLNs during lymphedema development, we treated mice with bestatin following surgery. Bestatin has previously been shown to ameliorate swelling through its pro-lymphangiogenic effects in the double vessel ligation mouse tail lymphedema while also partially rescuing lymphatic function . AdditioKetoprofen, a non-steroidal anti-inflammatory drug acting on the metabolism of arachidonic acid upstream of LTB4, has been tested as a treatment for lymphedema in a clinical trial ,41. KetoIt is also important to note that bestatin is used clinically to treat patients with chronic lymphedema, while our mouse model of lymphedema presents acute disease which eventually resolves. Chronic lymphedema is characterized by extensive and prolonged swelling, sustained tissue fibrosis and hardening, and adipose hypertrophy. These aspects of the disease are difficult to reproduce in animal models of acute disease, so our single vessel ligation model only recapitulates some aspects of the clinical manifestation of lymphedema. Potential benefits of bestatin on lymphatic function observed in this study may thus provide additional benefits in clinical lymphedema given that our model does not fully reproduce the chronic disease characteristics.While bestatin treatment did not reduce swelling or inhibit leukocyte expansion in the dLNs in our lymphedema model, it did increase NP accumulation within the intact vessel dLN as lymphedema progressed D. ThrougInterestingly, bestatin-treated mice showed significant differential leukocyte expansion between the dLNs at 2W compared to the saline control group A. Taken Through combining flow cytometry analysis of leukocyte populations in dLNs with novel NIR imaging techniques to quantify lymphatic transport, our work has begun to uncover the relationship between fluid uptake and immune cell involvement during lymphedema development. We show that differential NP transport into the dLNs during lymphedema development was correlated with differential leukocyte expansion in those dLNs B. Bestatn = 14), 1 week (n = 16), 2 weeks (n = 21), and 3 weeks (n = 15) after surgery.We used the single vessel ligation model of lymphedema developed in our lab where a pair of collecting vessels on one side of the mouse tail were left intact while the remaining dermal initial lymphatics and collecting vessels were ligated and cauterized . Eight-wg and decanting the liquid, Zombie Green live/dead solution  was added at room temperature for 30 min. Following a wash step, multiple antibodies conjugated to fluorophores were added to the suspensions for 30 min on ice. The antibodies used were APC anti-mouse F4/80 (1:40), APC/Cyanine7 anti-mouse Ly6G (1:100), Brilliant Violet 421 anti-mouse/human CD11b (1:33), Brilliant Violet 510 anti-mouse Ly6C (1:100), Brilliant Violet 605 anti-mouse CD3 (1:40), Brilliant Violet 711 anti-mouse CD64 (1:40), Brilliant Violet 785 anti-mouse CD19 (1:40), PE anti-mouse I-A/I-E (1:40), PE/Cy7 anti-mouse CD206 (MMR) (1:50), and PerCP anti-mouse CD11c (1:40) . After labeling with antibodies, 2% PFA was added for 15 min on ice to fix the cells. The stained cells were then stored in FACS buffer (10 mg/mL BSA in PBS) for analysis. A BD Fortessa Flow Cytometer was used to run the samples. UltraComp eBeads  were used for single-stain compensation controls. BD FACSDiva was used to record results and FlowJo was used for all analysis of results. Our flow panel did not include a stain for CD45, so leukocytes were defined as CD3+/CD19+/CD11b+/CD11c+/Ly6C+. The gating strategy implemented in FlowJo is shown in Both the sacral lymph nodes, which drain fluid from the tail, were harvested when mice were euthanized at 2 days, 1 week, 2 weeks, and 3 weeks after surgery. The lymph nodes were stored in a 1 mg/mL Collagenase D solution  and incubated at 37 °C for 1 h for disassociation. We then pushed the lymph nodes through a 70 μm cell strainer to create a single cell suspension. A CD16/32 antibody blocking solution  was added for 5 min on ice. After spinning down for 5 min at 350× Tail swelling was measured prior to surgery and when mice were euthanized. Tail images were taken using an iPhone camera with a ruler adjacent to the tail to provide a measurement reference and ImageJ was used to quantify swelling. The diameter of the tail was measured at 5–10 mm increments along the tail starting at the site of injury. The truncated cone method was used to determine the total volume of the tail given the diameters along its length. Percent volume change was measured by comparing the tail volume at endpoint to the volume prior to surgery.SH-NP were synthesized as previously described ,22,23,24A total of 10 μL of 680-NPs were injected intradermally into the mouse tail tip while the mouse was under anesthesia 24 hrs prior to euthanasia. After euthanasia, the sacral lymph nodes draining the mouse tail were harvested and placed into a black 96-well plate. The lymph nodes were then imaged using a customized imaging system consisting of a Sutter Instrument Lambda LS Xenon arc lamp , an Olympus MVX-ZB10 microscope , a 650 nm bandpass excitation filter , a 720 nm bandpass emission filter (60 nm FWHM), and a 685 nm longpass dichroic mirror. Images were acquired with a Photometrics Evolve Delta 512 EM-CCD . The two nodes were imaged in the same field of view using 1x magnification and an exposure time of 50 ms.Multiple metrics were used to quantify fluorescence in the lymph nodes. The maximum fluorescence of the lymph node was quantified as the maximum fluorescence value within the lymph node. The normalized mean fluorescence was quantified as the mean fluorescence within the lymph node subtracted by the mean background fluorescence of a window 50 pixels by 50 pixels located away from the lymph node. The normalized sum of fluorescence was calculated as the normalized mean fluorescence multiplied by the area of the lymph node in pixels.n = 15), 2W (n = 18), and 3W (n = 12) after surgery.Bestatin treatment started at three days after surgery, as a previous study showed that beneficial effects of bestatin treatment were dependent on starting the treatment at this time . To makeNIR lymphatic imaging was performed according to previously published methods ,27,28,29For comparison of leukocyte populations in the draining lymph nodes among the various timepoints analyzed, Kruskal–Wallis tests with Dunn’s multiple comparisons tests were used. Spearman’s rank correlation was used to calculate correlations between swelling percentage and various leukocyte populations. Fluorescent measurements from the 680IR NP experiments were transformed using the natural logarithm to create a normally distributed dataset. Ordinary one-way ANOVA tests with Tukey’s multiple comparisons tests were then used to compare between timepoints. Kruskal–Wallis tests with Dunn’s multiple comparisons tests were used to compare the normalized difference of leukocyte populations in intact versus injured lymph nodes between timepoints. Linear regression was used to calculate correlations between normalized difference and fluorescent measurements. A mixed-effects model with Šídák’s multiple comparisons test was used to compare normalized lymphatic fluorescence transport from the NIR imaging measurements between the timepoints analyzed. Two-way ANOVA test with Šídák’s multiple comparisons tests were used to compare the natural logarithm of fluorescent measurements from the 680IR NP experiments between saline and bestatin-treated mice at each timepoint. The NP fluorescent measurements were transformed using the natural logarithm to create a normal distribution of the data. Multiple linear regression was also used to investigate how NP fluorescence metrics correlated with both treatment and timepoint. The multiple linear regression model used the natural logarithm of the NP fluorescence metric as the dependent variable, with treatment and timepoint as the independent variables. The least-squares regression included terms for both independent variables and the interaction between them. Multiple Mann–Whitney tests using the Holm–Šídák method were used to compare leukocyte populations in draining lymph nodes between saline and bestatin-treated mice at each timepoint. Multiple Mann–Whitney tests using the Holm–Šídák method were used to compare normalized difference between saline and bestatin-treated mice at each timepoint. GraphPad Prism was used for all statistical analysis.


Ectopic pregnancies develop outside of the uterus and lead to significant maternal morbidity and mortality if they rupture. As the primary diagnostic tool for these presentations, ultrasound has a growing list of signs and measurements that help distinguish between intrauterine and ectopic pregnancies, the latter being exceedingly rare once a woman has entered her second trimester. The present case reports a series of Emergency Department visits by a woman carrying a second-trimester pregnancy—deemed intrauterine on transabdominal ultrasound due to gestational age and location—who developed massive hemoperitoneum and was diagnosed with a ruptured 15-week tubo-ovarian pregnancy on laparotomy. The discussion describes the sonographic findings that could have helped make the proper diagnosis, most notably mantle distance—the thickness of the myometrium surrounding the gestational sac—which would have correctly identified this pregnancy as ectopic. Ectopic pregnancy (EP) is a potentially life-threatening complication that occurs in 1-2% of pregnancies . Tubal pOver the course of 9 days, a 38-year-old G2P0020 female with history of asthma presented to the Emergency Department three times with abdominal pain. She reported her last menstrual period was two months ago and denied any vaginal bleeding. Her abdomen was tender on exam, but no peritoneal signs were appreciated. Her initial blood pressures (BP) were 96/61 mmHg on visit 1, 86/62 mmHg (visit 2), and 88/58 mmHg (visit 3). She was never tachycardic. Initial labs revealed a urinary tract infection and Trichomonas infection, for which she was prescribed antibiotics. During her first visit, bedside transabdominal ultrasound (TAUS) with the probe placed in the suprapubic region revealed a fetus estimated to be 14 weeks, 2 days old by biparietal diameter . The fetWhile there are multiple cases reporting ruptured first-trimester EPs, Liu et al. conducted a 2013 review and only identified 16 published cases of tubal pregnancies diagnosed in the second trimester, dating back to 1951 . Tubal r


Metagenomic sequencing of microbial cell-free DNA (cfDNA) in blood and urine is increasingly used as a tool for unbiased infection screening. The sensitivity of metagenomic cfDNA sequencing assays is determined by the efficiency by which the assay recovers microbial cfDNA vs host-specific cfDNA. We hypothesized that the choice of methods used for DNA isolation, DNA sequencing library preparation, and sequencing would affect the sensitivity of metagenomic cfDNA sequencing.We characterized the fragment length biases inherent to select DNA isolation and library preparation procedures and developed a model to correct for these biases. We analyzed 305 cfDNA sequencing data sets, including publicly available data sets and 124 newly generated data sets, to evaluate the dependence of the sensitivity of metagenomic cfDNA sequencing on pre-analytical variables.Length bias correction of fragment length distributions measured from different experimental procedures revealed the ultrashort (<100 bp) nature of microbial-, mitochondrial-, and host-specific urinary cfDNA. The sensitivity of metagenomic sequencing assays to detect the clinically reported microorganism differed by more than 5-fold depending on the combination of DNA isolation and library preparation used.Substantial gains in the sensitivity of microbial and other short fragment recovery can be achieved by easy-to-implement changes in the sample preparation protocol, which highlights the need for standardization in the liquid biopsy field. The observation that microbial cell-free DNA (cfDNA) is present in biofluids has inspired new avenues for infectious disease testing . Recent Synthetic cfDNA was prepared by shearing  ΦX174 RF I DNA (NEB) at a concentration of 1 μg/μL in Tris-EDTA, pH 8.0, to 5 target fragment lengths  and mixed such that the resulting fragment length profile exhibited a smooth, broad distribution  . SampleSamples were quantified using the Qubit dsDNA HS Assay  and characterized using the AATI Fragment Analyzer HS NGS Fragment Kit (Agilent) before and after each assay. Length traces were adjusted to account for library preparation adapter sequences and normalized using the bayestestR package (method = “trapezoid”) ,17. The The transfer function for each unique workflow combination of cfDNA isolation, library preparation, and sequencing [obtained from ] was proOne hundred and forty-two urine samples were collected from 83 kidney transplant recipients who received their transplant at New York Presbyterian Hospital-Weill Cornell Medical Center (kidney transplant patients), with 30 of these samples evaluated using different cfDNA isolation or library preparation methods . This stg on the same day for 30 min and the supernatant was stored in 1 mL aliquots at −80°C. For the tuberculosis patient samples, 10 mL of urine was mixed with 2 mL Streck cell-free DNA urine preserve  and centrifuged at 3000g for 30 min at ambient temperature. The supernatant was similarly stored in 1 mL aliquots at −80°C.Samples were collected via the conventional method for a clean-catch midstream specimen used for standard urine culture. For the kidney transplant patient samples, approximately 50 mL of urine was centrifuged at 3000g for 10 min within 24 h after blood collection. Plasma was stored in 1 mL aliquots at −80°C. All individuals provided written informed consent.Additionally, 40 plasma samples from 6 individuals receiving double-lung transplants at Stanford University Hospital collected in the scope of a previous study were included (lung transplant recipients) , 12. BriTo evaluate the performance of different kits for various downstream applications, we analyzed the performance of spin column- and magnetic bead-based commercial kits targeted for cfDNA or short fragment isolation. Urinary cfDNA and synthetic cfDNA samples were isolated and libraries were prepared using the kits detailed in The Qiagen CNA kit was chosen as the gold standard reference for the cfDNA isolation assays because it was previously shown to be the most consistent and efficient cfDNA isolation kit . The NorThe extraction master mix was made with 1.25 mL MagMax lysis/binding solution, 0.5 mL isopropanol, and 7.5 μL MagMax beads per 1 mL sample.After combining the appropriate volumes of extraction mix and urine, samples were rotated on a rotisserie inverter for 30 min at room temperature.The cfDNA was eluted from beads in 50 μL MagMax DNA elution solution prewarmed to 55°C by vortexing in a heated shaker at 1400 rpm, 55°C for 20 min.The second bind–wash–elute steps were removed from the workflow.Single -stranded sequencing libraries were prepared either as previously described  or usingMycobacterium tuberculosis H37Rv (edited from NC_000962.3) and the circularized Escherichia coli (edited from NZ_CP027599.1) genomes. The lengths for reads aligning to the chromosomal, mitochondrial, and microbial genomes with a minimum mapping quality of 30 and minimum insert size of 45 bp were calculated as the absolute difference between the start and end coordinates of the mapped read. The measured fragment length density profile was computed using the hist function from the R graphics package for lengths 25 to 500 bp.Low-quality bases and Illumina-specific sequences were trimmed  . Reads wks.test function in the standard stats package in R.To compute the intrinsic fragment length profile, the measured distributions were first scaled to the input biomass and then multiplied with the relevant transfer function across all fragment lengths. The convergence of the cumulative distributions was evaluated using the Samples with culture-confirmed urinary tract infection were chosen to evaluate the effects of cfDNA isolation and library preparation on microbial enrichment. Two aliquots from each of 10 samples were subject to isolation using the CNA kit in combination with either the NEB or SRSLY library preparation kit. An additional 2 aliquots from another set of 20 samples were each subject to a unique cfDNA isolation kit followed by library preparation using the Meyer protocol . All theTo calculate the expected MPM, we first evaluated the expected effect of each kit on the host and microbial fragment length profiles by taking the product of the appropriate transfer function and the intrinsic density. The yield was then quantified as the area under the curve of the transformed profile using the bayestestR package (method = “trapezoid”) , and theAll statistical analyses were performed in R 3.5.0. Boxes in the boxplots indicate the 25th and 75th percentiles, the band in the box represents the median, and whiskers extend to 1.5 x interquartile range (IQR) of the hinge. The sequence data for the kidney transplant recipient cohort was deposited in the NCBI database of Genotypes and Phenotypes . The sequence data for the lung transplant cohort was deposited in the NCBI Sequence Read Archive (accession no. PRJNA263522). The sequence data generated in the scope of this study will be deposited in the NCBI Sequence Read Archive.Metagenomic cfDNA sequencing assays follow 3 major experimental steps: isolation of the DNA from the biofluid, DNA sequencing library preparation, and DNA sequencing. The efficiency of each of these steps is dependent on the DNA fragment length, and therefore each of these steps introduces fragment length-related biases. The distribution of DNA fragment lengths measured after sequencing is the product of the intrinsic fragment length profile of the original cfDNA sample and the transfer functions of the experimental procedures used, where a transfer function is computed as the yield of the experimental procedure over all fragment lengths. We set out to characterize the transfer functions of 5 different commercial kits for cfDNA isolation, 1 protocol for double-stranded DNA library preparation, and 2 protocols for single-stranded DNA library preparation to better understand the measurement biases they introduce .To create measurement bias models, we mixed isolates of ΦX174 RF I DNA sheared to 5 target lengths to create a DNA sample that exhibited a broad, smooth fragment length profile ranging from 0 to 500 bp . This syThere were clear differences in the transfer functions of different DNA isolation and library preparation procedures. Three of the DNA isolation kits  exhibited a relatively flat transfer function , while the other two kits (Norgen and QiaQuick) displayed a strong bias towards shorter DNA fragments, with yields up to 100% for fragments shorter than 100 bp . The libTo assess the length biases introduced in metagenomic cfDNA sequencing by different DNA isolation kits, we measured the fragment length profiles of chromosomal, mitochondrial, and microbial cfDNA in the urine of individuals with urinary tract or tuberculosis infection. We performed paired-end DNA sequencing for a total of 124 urinary cfDNA samples that were prepared using different combinations of cfDNA isolation and library preparation protocols, and analyzed an additional 181 data sets of matched samples that were produced with our reference workflow in the scope of prior studies , 12, 14.To obtain the intrinsic fragment length distribution of urinary cfDNA, we corrected the measured distributions with their appropriate transfer function. This resulted in convergence to a single fragment length profile for chromosomal, mitochondrial, and microbial cfDNA  and 2. SE. coli = 4, Pseudomonas aeruginosa = 2, Enterococcus faecalis = 3, Klebsiella pneumonia = 2). Two aliquots of each sample were subject to cfDNA isolation using one of the remaining 4 kits followed by library preparation with the Meyer protocol. We used previously established bioinformatics approaches to quantify microbial- and host-specific reads and computed the MPM relative to the CNA kit . cfDNA was isolated from 2 aliquots per sample using the CNA kit and library preparation was performed using either the NEB or SRSLY kit. We used the experimental transfer functions to unskew the measured fragment length distributions, which did not yield a single, converged fragment length profile (We next experimentally tested the effect of different library preparation procedures on the relative yield of microbial vs host specific cfDNA. We selected samples from 10 patients diagnosed with urinary tract infection by conventional culture ( profile . This obWe calculated the relative number of microbial reads that resulted from the different library preparations and found that the length bias model for library preparation protocols were not predictive : the modIn this study, we show that the measured fragment length distributions of urinary and plasma cfDNA and the recovery of microbial- and host-specific cfDNA are dependent on the choice of pre-analytical variables. Data distortions due to cfDNA isolation can be accounted for by transfer functions which, when applied to measured fragment length distributions, produce a common underlying fragment length distribution. Correction for fragment length biases yields a single distribution that is very short, with a mean fragment length <100 bp for both host- and microbe-specific cfDNA.The performance and sensitivity of a metagenomic sequencing assay is directly correlated with the microbial enrichment over host reads. The cfDNA isolation transfer functions readily account for these differences, with kits favoring shorter fragments recovering over 3-fold more clinically reported microbial reads per human read. However, the sequencing library preparation protocols do not tell a similar, straightforward story. Fragment length biases only partially account for practical differences in library preparation methods, suggesting that the physical configurations of cfDNA constitute another driving force. Because both single-stranded library preparation protocols outperformed the double-stranded library preparation assay in terms of microbial enrichment, we believe that these differences lie in the sensitivity of each assay to different DNA conformations. The double-stranded library preparation protocol is effective at capturing blunt-ended double-stranded fragments, like the synthetic sample used to characterize the transfer functions, but is insensitive to the gamut of forms that might be found in a cfDNA sample. Single-stranded library preparation methods are more sensitive to the full range of conformations present in cfDNA samples, which may contain nicks, fragments with overhangs, and single-stranded DNA . Our stuOur work underscores the importance of considering multiple biases introduced in the sample preparation workflow to achieve highly sensitive metagenomic cfDNA sequencing assays. It further demonstrates the need for standardization in the liquid biopsy field, particularly in cases where metagenomic cfDNA sequencing is used to guide clinical decisions or where the biophysical properties of cfDNA are used to inform diagnostic technology development. Our findings are relevant for cfDNA applications in prenatal testing and cancer screening, where differences in fragment lengths have been leveraged to improve diagnostic performance , 33–38.Clinical Chemistry online.hvab142_Supplementary_DataClick here for additional data file.


Mustela putorius furo) were trained to display a specific conditioned behavior  in response to feces from AIV-infected mallards in comparison to feces from healthy ducks. In order to establish that ferrets were identifying samples based on odors associated with infection, additional experiments controlled for potentially confounding effects, such as: individual duck identity, housing and feed, inoculation concentration, and day of sample collection (post-infection). A final experiment revealed that trained ferrets could detect AIV infection status even in the presence of samples from mallards inoculated with Newcastle disease virus or infectious laryngotracheitis virus. These results indicate that mammalian biodetectors are capable of discriminating the specific odors emitted from the feces of non-infected versus AIV infected mallards, suggesting that the health status of waterfowl can be evaluated non-invasively for AIV infection via monitoring of volatile fecal metabolites. Furthermore, in situ monitoring using trained biodetectors may be an effective tool for assessing population health.Outbreaks of avian influenza virus (AIV) infection included the spread of highly pathogenic AIV in commercial poultry and backyard flocks in the spring of 2015. This resulted in estimated losses of more than $8.5 million from federal government expenditures, $1.6 billion from direct losses to produces arising from destroyed turkey and chicken egg production, and economy-wide indirect costs of $3.3 billion from impacts on retailers and the food service industries. Additionally, these outbreaks resulted in the death or depopulation of nearly 50 million domestic birds. Domesticated male ferrets ( The idea that changes in body odor alterations can be diagnostic for disease diagnosis has been around since the time of Hippocrates (around 400 bce). Extending this concept to the surveillance of disease in wildlife populations is relatively new in comparison but is gaining support as more evidence is presented that certain infectious diseases can alter human and animal body odors. Efforts to exploit this phenomenon have increased, with multiple demonstrations that such biodetectors are accurate and efficient in the detection and surveillance of disease , 2.Due to devastating losses of farmed fowl, AIV has been identified for its potential to disrupt the economy of the poultry industry , 4. WateIn a preliminary study, we demonstrated that ferrets could be trained to display a specific conditioned behavior  in response to a marked increase of acetoin when presenting varying ratios of acetoin (3-hydroxy-2-butanone) and 1-octen-3-ol which were diagnostic of AIV infection. After successfully completing this discrimination task, ferrets rapidly generalized this learned response to the odor of feces from AIV- infected mallards. This confirmed earlier research using trained mice to discriminate infection status of ducks on the basis of fecal odors . In thisWe hypothesized that successful AIV detection by trained mice could be repeated in a species that had a more malleable behavioral repertoire, specifically dogs. Toward our plans for developing a viable biodetector program, ferrets were first chosen as a “bridge” to evaluate the concept. Ferrets were chosen on evidence that domestic ferrets readily learn discrimination tasks and exhibit dog-like social-cognitive skills when interacting with humans , 12 and Mustela putorius furo) were trained to display a specific conditioned behavior  in response to feces from mallards experimentally infected with low pathogenic AIV. Ferrets were able to discriminate samples from infected versus noninfected ducks in several experiments. Bioassays were performed to control for potentially confounding effects such as individual duck identity, virus infection dose, and infection day . Furthermore, we evaluated if ferrets generalized the learned LPAIV response to other viruses. This test of specificity was a critical evaluation of the utility of trained biodetectors for field evaluation.In the current study, domesticated male ferrets  and the protocols for experimental infection were approved by the National Wildlife Research Center (QA-1912) and the Colorado State University (17-7544A) Institutional Animal Care and Use Committees.ad libitum access to tap water and Totally Ferret Complete diet  with the exception of food restriction periods during training and testing.Six castrated male ferrets were acquired at 15 weeks of age from Marshall BioResources  and trained as described in a previous study (PONE-D-20-11704R1). Ferrets were pair-housed at the National Wildlife Research Center  in two level wire cages  and maintained at 23°C on a 12 hour light (12 hour dark) cycle. The ramp connecting the upper and lower levels of the cage could be locked in a closed position, allowing each of the ferrets to be isolated. Environmental enrichment was provided both in the cages  and during 60 minute free exercise periods daily on weekdays. Ferrets were given During food restriction periods, ferret body masses were recorded every weekday and health was assessed daily . There was no food restriction on weekends and ferrets were assessed for health daily by Animal Care staff. Food was provided after training or testing sessions for 1 hour while the ferrets were separated on different levels of the cages. Food bowls were weighed before and after the feeding session and the difference  was recorded. Food and/or water restriction has been shown to be required for reliable operant conditioning responses in rats and minimally stressful in terms of behavior, appearance and physiology , 15. Ferad libitum. Feed consisted of game bird chow and cracked corn mixture (mixed 2:1). All birds were maintained in containment prior to experimentation and were screened for antibodies to IAV prior to inoculation to ensure they were negative. Testing occurred in BSL-2 containment rooms. All ducks were inoculated oro-choanally with 1 ml of BA-1 viral transport media  containing 0, 3, 4 or 5 log10 EID50 of A/environment/Illinois/NWRC183983-24/2006 . H5 (next cohort) and H6 viruses were used in these experiments because those subtypes are of high interest due to the increased likelihood that those subtypes spillover into poultry and cause economic harm. While H3s and H4s are the most commonly detected subtypes in N American waterfowl and can spillover into poultry, H3s and H4s do not generally cause pathogenicity in wild birds or poultry. Mallards were inspected daily for signs of pain or distress. Feces were collected from individual ducks daily on days 0, 1, 2, 3, 4, 7, 10, and 14 post-inoculation stored at -80°C until testing. All ducks were also swabbed and tested for viral RNA per qPCR methods described in [Sixty mixed sex hatchery-bred mallards  were randomly assigned to one of four treatment groups of 15 ducks each. Fresh water and food were provided ribed in  which co6 plaque-forming units (pfu) of A/Mallard/MN/346250/00 (H5N2). Cloacal swabs were collected on days three and four following experimental infection. All individuals were inspected daily for signs of pain, distress, or infection. Infection was confirmed by real-time RT-PCR and inoculation into 10-day old embryonating chicken eggs. Two pooled fecal samples were collected from each duck. Feces were collected daily for four days immediately preceding experimental infection and again on days 1, 3, 5, 7, 9, 11, and 13 post-inoculation. Pre- and post-treatment samples were stored frozen at -80°C until training and testing.Ten farm-raised mallards of mixed sex were housed indoors (10 birds per pen). Fresh water and food were provided daily. Feed consisted of approximately100g of game bird chow and cracked corn mixture (mixed 2:1) per duck per day. All birds were maintained in containment prior to experimentation and were screened for antibodies to IAV prior to inoculation to ensure they were negative. Six ducks were infected ocularly, intranasally and orally with 1 ml of brain heart infusion broth containing 1.6 x 1050) of a lentogenic, field isolate of Newcastle disease virus (NDV). At the same time, another 10 ducks in a different room were inoculated with 20,000 TCID50 of a field isolate of infectious laryngotracheitis virus (ILV). For birds inoculated with either virus, cloacal swabs and feces were collected prior to virus inoculation and daily from days 1–5 following virus inoculation. Ten ducks were not inoculated and used as controls. Infection was confirmed by virus specific plaque assays of tracheal swab samples.Twenty farm-raised mallards of mixed sex were housed indoors (10 birds per biocontainment room). Housing, water, and food were provided consistent with LPAIV infected mallards. Ten ducks were infected by intratracheal inoculation of 0.15 ml containing 50,000 tissue culture infectious doses 50% , and picked up the board to position the boxes for the next trial. The ferret handler controlled when the ferrets were to start a trial, called out when a ferret alerted to one of the boxes, rewarded the ferret if the coordinator confirmed the choice , or picked up the ferret and walked away if the coordinator called the choice incorrect, and then faced away from the coordinator while the board was prepared for the next trial. This method was used for all trials that included the shaping of behavior, training, and experimental testing, specifically during rewarded trials but not during unrewarded trials.A single daily session consisted of 12 trials. During initial training all correct selections were rewarded in all 12 trials. Once all ferrets demonstrated 75% accuracy in rewarded training trials, four extinction (training) or four generalization (testing) trials were introduced into each session . The numbers of rewarded/unrewarded trials were determined experimentally in a previous study (PONE-D-20-11704R1) and based on instrumental learning theory. Extinction trials were no different than training trials except that the ferrets were not rewarded for correct selections. Whereas the stimuli presented during extinction trials were the same fecal samples that are presented in rewarded training trials, unrewarded generalization trials consisted of novel (a condition or design element that the ferrets had not previously experienced) stimuli. Because the ferrets experienced a neutral response from the handler immediately following an extinction or a generalization trial, we assumed that little or no learning occurred during these trials. An overview of the training and testing that used these methods can be found in 10 EID50 H6N2 inoculation dose groups representing all collection days  where real time RT-PCR revealed ongoing viral shedding. We assumed these were the optimal sample days to use where there should be ongoing odor signals the ferrets were likely using as cues that were due to viral induced metabolic changes.To train ferrets to respond to fecal samples from novel individual ducks and inoculation doses for mallards infected with LPAIV, rewarded trial CS+ samples consisted of fecal samples from novel individual ducks from the 3 or 5 logCS- samples consisted of samples from randomly chosen novel uninfected control individual ducks representing all collection days (days 0–14). Following two days of all rewarded training trials, we introduced unrewarded trials into the sessions. One session group that included four days of extinction trial sessions (n = 96) and a second session group that included three days of extinction trial sessions (n = 72). In the second session group, extinction trial CS+ samples consisted of samples from familiar ducks representing novel collection days (days 2–14) for that individual . That is, CS+ samples used in the extinction trials were from the same ducks, but different collection days than previously used.Each daily session included four extinction trials and eight rewarded trials per ferret randomly presented during twelve trials per session. The same fecal samples were used across all four days. After four days, the ferrets were performing at 85% or better and were able to move onto the next stage of testing with further extinction trials. The next three days of testing sessions used fresh samples from the same ducks, but novel collection days and consisted of 72 overall unrewarded extinction trials across the 6 ferrets, again with four extinction trials per ferret per day. After three days of this level of training, ferrets were performing at 85% or better. The performance at the end of these training trials indicated the ferrets were ready for testing sessions with novel samples  presented in unrewarded generalization trials.10 EID50 doses representing collection days 2–14. Generalization trial CS+ samples consisted of novel individual ducks inoculated with the 4 log10 EID50 dose and representing collection days 2–14. Generalization CS- samples consisted of control ducks representing collection days 1–14 and collection day 0 samples from infected ducks.The ferrets’ response to samples collected from novel ducks was examined in unrewarded generalization trials interspersed among rewarded trials. Rewarded trial CS+ samples consisted of randomly chosen novel individual ducks inoculated with the 3 or 5 log10 EID50 were being selected as CS+ at rates higher than anticipated. Despite a relatively high-performance mean accuracy of 81%, during these trials, we noticed that individual ferrets making the most errors were choosing the fecal samples from specific individual donors . We removed from testing and training all day 0 fecal samples from these specific donors because of these confounding effects .Rewarded trial CS- and CS+ samples consisted of randomly chosen control or infected fecal samples from individual ducks representing collection days 3–14. Generalization trial CS- samples consisted of samples from control ducks with 3 sample boxes representing collection days that matched the collection day of the CS+ . The fouIn order to further challenge the hypothesis that ferrets were merely choosing the sample that differed the most from the other samples, two CS+ samples from different individual ducks and with differing collection days from each other and from the CS- samples were included in the panel configurations for the generalization trials. All rewarded trial samples were from collection days 4–14 with CS- samples from control ducks and CS+ samples from infected ducks (any inoculation dose group). Generalization CS- samples consisted of control duck samples from the same collection day. Generalization CS+ samples were from two individual infected ducks from the same or differing collection days . This poAdditional generalization trials were conducted in which the 3 CS- samples and a CS+ sample presented were all from the same collection day and a second CS+ sample was from a differing collection day. Thus, only the odd CS+ had a different collection day in comparison to the remaining samples with the exception of trials with all the same collection day . RewardeWe collected pre and post infection samples from a new cohort (cohort 2) of mallards reared and subsequently infected at CSU for use in unrewarded generalization trials. Feces from cohort 1 were used in rewarded trials. We ran these panel configurations for two days, resulting in 48 unrewarded generalization trials across the six ferrets.To determine if ferrets trained to detect an odor representative of LPAIV infection would generalize to fecal samples collected from ducks infected with a different virus, we conducted generalization trials with one control fecal sample from each duck cohort, a post NDV infection sample, a post ILTV infection sample, and one CS+ sample from a LPAI-infected duck  after a Cumulative responses across all trained ferret trials were calculated for each set of experimental generalization trials. Success rates  were statistically evaluated using binomial proportion tests with a continuity correction for small numbers of observations . The datThe first four day extinction trial sessions were conducted to determine if the performance of the ferrets was accurate enough to move on to testing. The first day, the accuracy performance of individual ferrets ranged from 67–92% . By day 2, the ferrets were performing at 93% accuracy with individual ferret performances ranging from 92–100%. By day 4, the ferrets were still performing at 93% accuracy overall with individual ferret performances ranging from 75–100%. The next three days of double-blind testing used fresh samples from familiar individual duck donors, but novel collection days, resulted in 72 overall unrewarded generalization trials. The first day, the accuracy performance of individual ferrets ranged from 75–92%. By day 3, the ferrets were performing at 96% accuracy with individual ferret performances ranging from 83–100%. Interestingly, when the ferret response to positive samples is compared to viral RNA equivalents EID50/mL as confirmed by calibrated qPCR , the ferTrained ferrets were highly accurate  at discriminating between fecal samples collected from control mallards and from mallards across the entire spectrum of collection days , exposure dosage, individual duck identity, or husbandry methods. Nonetheless, important questions remain to be answered. For example, can a biodetector detect the difference between fecal samples from waterfowl infected with HPAIV from LPAIV, or differentiate between samples that result from infection with different subtypes or strains of AIV? Most importantly, it will be interesting to determine whether a biodetector trained to identify LPAIV in mallard fecal samples and identify the odor identity of AIV in another species. This study clearly demonstrates the feasibility of deploying trained biodetectors for AIV surveillance in waterfowl.


Tumor infiltration by T cells is paramount for effective anti-cancer immune responses. We hypothesized that the T cell receptor (TCR) repertoire of tumor infiltrating T lymphocytes could therefore be indicative of the functional state of these cells and determine disease course at different stages in cancer progression. Here we show that the diversity of the TCR of tumor infiltrating T cell at baseline is prognostic in various cancers, whereas the TCR clonality of T cell infiltrating metastatic melanoma pre-treatment is predictive for activity and efficacy of PD1 blockade immunotherapy. Precision medicine needs prognostic markers to select the patients that will benefit more from targeted therapy. Authors show here that high level of baseline T cell receptor diversity is an indicator of favourable prognosis in multiple cancer types, and monoclonal expansion of T-cells correlates with good response to immune checkpoint blockade therapy in metastatic melanoma patients. Unfortunately, the identification of the patients who will benefit from treatment remains an unmet need, so to refine patient care predictive biomarkers are required to identify metastatic patients with better chances of responding to CPB. Moreover, in the adjuvant setting, tools are needed to select patients at lower risk of disease recurrence who have been cured by surgery so that they can be spared the risk of CPB-associated toxicity. The first biomarker strategies to emerge focused on the quantification of the tumor mutational burden and the expression of PD1 ligand (PD-L1) in the tumor microenvironment, but additional tools are needed to improve accuracy and the distinction between prognostic and predictive biomarkers3.Immunotherapy with programmed death 1 (PD1) checkpoint blockade (CPB) is increasingly utilized to treat solid tumors in the metastatic setting, where the response rate is 20–55%4. We recently reported that immune checkpoint inhibition with PD1 CBP can increase the clonality or the diversity of the TCR in peripheral T cells after 3 weeks of treatment, and importantly this bifurcated reaction only occurs in patients who respond to treatment5. This approach therefore allows patient responses to be monitored using minimally invasive liquid biopsies early during treatment.The highly variable complementarity determining region 3 (CDR3) of the beta chain of the T cell receptor (TCR) is unique to individual T cell clones and can therefore be used to monitor the dynamics of T cell repertoire responses to CPBHere we examine whether the TCR repertoire metrics in tumor-infiltrating T lymphocytes (TIL/Tc) can also identify which patients will benefit from CPB prior to commencement of therapy.P = 0.0401, hazard ratio = 4.8 × 10−14, C-index = 0.88) correlated to high TCR clonality in these pre-treatment tumor samples  and targeted TCR sequencing) used to reconstruct the TCR in these melanoma cohorts and also with no significant difference in the overall TIL/Tc clonality, although TCR reconstruction from the RNA-Seq data yielded overall fewer unique TCR clonotypes than from the targeted TCR sequencing 13 were prognostic for OS . To quantify cumulative melanoma risk based on these findings, we developed a nomogram to assist clinical decisions  melanoma cohorte 7 SBS7v13 were pe 7 SBS7v13 were pons Fig.  and provons Fig. .Fig. 2TI14, we restricted our LUSC analysis to patients with low cigarette use, and due to insufficient OS events15, we used progression-free interval as the TGCT endpoint. Also, due to the small number of events for patients with TCR data, we could not perform regression analysis for THYM15. Despite these restrictions, we found that high TCR diversity in the TIL/Tc was associated with improved survival in all of these cancers , which includes breast cancer (BRCA), melanoma (SKCM), squamous lung carcinoma (LUSC), lung adenoma (LUAD), thymoma (THYM), clear cell renal cancer (KIRC), and testicular cancer (TGCT) , the need for predictive and prognostic stratification tools for CPB is becoming more pressing. This is particularly important for patients with intermediate-risk disease where the odds of toxicity could outweigh the benefit of adjuvant immunotherapy and where the TIL/Tc repertoire could provide a much-needed reliable biomarker for patient selection.More studies are needed to determine why high TIL/Tc clonality is predictive of CPB benefit, whereas TIL/Tc diversity is prognostic in the absence of CPB, but our findings nevertheless have important clinical implications because of their potential to contribute to the development of personalized therapeutic strategies through the identification of the patients who could better benefit from treatments.The training cohort patient samples do not involve clinical trials/clinical trial-associated data, as patient samples were collected prior to standard-of-care treatment. Biopsy pre-treatment samples from Manchester patients were prospectively collected under the Manchester Cancer Research Centre (MCRC) Biobank ethics application #18/NW/0092; the study was approved by MCRC Biobank Access Committee application 13_RIMA_01. Biopsy pre-treatment samples and clinical information from Padova patients were collected under the University of Padova Department of Surgery, Oncology and Gastroenterology ethics application 04/03/2002 protocol #448 and Veneto Oncology Institute ethics approval 09/04/2018 protocol #006264. Biopsy pre-treatment samples from Meldola patients were collected under ethics application #5483/2018 of Comitato Etico della Romagna. All patients gave written informed consent to the use of the samples for research purposes. Clinical endpoints: date of death was obtained from clinical records (pre-CPB training cohort), the original publications , and TCGA clinical information files. Radiological response information was obtained from the original publications.17, the human reads were aligned to GRCh37 (release 75) using STAR (v2.5.1) aligner18.RNA was extracted from pre-treatment human fresh frozen tumor samples using the AllPrep DNA/RNA Kit  according to the manufacturer’s instructions: briefly, tissue samples were first lysed and homogenized in a highly denaturing guanidineisothiocyanate-containing buffer to inactivate DNases and RNases and ensure isolation of intact DNA and RNA; the lysates were then passed through an AllPrep DNA membrane that, in combination with the high-salt buffer, binded the genomic DNA that was then eluted; ethanol was added to the flow-throughs from the AllPrep DNA membrane to provide appropriate binding conditions for RNA, and the samples were then applied to an RNeasy membrane; total RNA binded to the membranes and contaminants were washed away; high-quality RNA was then eluted in 45–70 μl water. Indexed PolyA libraries were prepared using 200 ng of total RNA and 14 cycles of amplification with the Agilent SureSelect Strand Specific RNA Library Prep Kit for Illumina Sequencing . Libraries were quantified by quantitative PCR (qPCR) using the KAPA Library Quantification Kit for Illumina platforms . Paired-end 100 bp sequencing was carried out by clustering 15 pM of pooled libraries on the cBot and sequenced on the Illumina HiSeq 2500 in high output mode using TruSeq SBS V3 chemistry ; average of all samples was 68 million pass-filter (PF) reads (each end). The primers were all supplied as part of the kits that are listed. After removing adapters using Cutadapt (v1.14) and trimming poor quality base calls using Trimmomatic (v0.36)11 for the 29 TCGA cohorts were kindly made available by the authors; the clinical data for the cohorts were downloaded from cBioportal in February 2018. CDR3 TCR sequences were inferred from RNA Seq data from pre-treatment biopsies for the training cohort samples using ImReP19; inclusion criterion for downstream analyses was minimum four TCR sequences identified. Clonality was calculated with the function clonality from LymphoSeq R package; heatmaps were generated using LymphoSeq, pheatmap, and ggplot2 R packages. The diversity was calculated using Renyi index (α = 1) as per Spreafico et al.20.CDR3 TCR sequence data generated by Bo Li et al.Whole-exome sequencing snap-frozen tumor tissue was manually dissected by sectioning (25-μm thick), and DNA was extracted from sections with an estimated tumor cell percentage of at least 80% using the AllPrep DNA/RNA Kit (Qiagen) according to the manufacturer’s instructions, as per description above. Germline DNA was isolated from patients’ blood. DNA quantity was assessed using a Qubit® 2.0 Fluorometer (Life Technologies).One microgram of genomic DNA was sheared using a Covaris S2 ultrasonicator . Multiplexed libraries were prepared using the SureSelectXT Target Enrichment System for Illumina Paired-End Sequencing and the SureSelect Human All Exon V6 Capture Library .21 (v1.1.7). Variant Effect Predictor (Ensembl version 73/84) was used to annotate the mutations. Known variants present in dbSNP were excluded.Libraries were quantified by qPCR using the KAPA Library Quantification Kit for Illumina platforms . Paired-end 100 bp sequencing was carried out by clustering 14 pM of pooled libraries on the cBot and sequenced on the Illumina HiSeq 2500 in high output mode using TruSeq SBS V3 chemistry ; average PF reads (each end) was 126 million for tumor samples and 67 million for germline samples. The primers were all supplied as part of the kits that are listed. After removing adapters using Cutadapt (v1.14) and trimming poor quality base calls using Trimmomatic (v0.36), the reads were aligned to the GRCh37 (release 75) human genome using BWA aligner (v0.7.7). The PCR duplicate reads were filtered using Picard (v1.96), and the base quality score recalibration and local INDEL realignments were performed using GATKtools (v3.1). Using tumor–normal pairs, SNVs were identified using MuTect12 package using default parameters. Signatures with contribution weights <6% were excluded.Mutational signatures for TCGA SKCM cohort were determined by fitting somatic SNVs with tri-nucleotide context to the 30 COSMIC mutational signatures using deconstructSigsPre-treatment biopsy samples were fixed in 10% neutral buffered formalin (Sigma-Aldrich), processed, and embedded in paraffin wax. Samples were sectioned (4 μm) and stained with hematoxylin and eosin using standard protocols. Formalin-fixed paraffin-embedded sections were deparaffinized using xylene and rehydrated passing through a series of graded ethanol to distilled water steps. Heat-induced epitope retrieval  was performed using a Pascal pressure chamber (Dako) with Dako target retrieval solution pH 6 . Sections were then processed and stained with anti-PD-L1 22C3 PharmDx  as per the manufacturer’s instructions: briefly, after peroxidase block for 5 min, the sections were incubated with the 22C3 antibody using a concentration of 1:50 for 60 min at room temperature and then incubated for 30 min at room temperature with the linker antibody provided with the kit and specific to the host species of the primary antibody; finally, the sections were incubated with a ready-to-use visualization reagent provided with the kit and consisting of secondary antibody molecules and horseradish peroxidase molecules coupled to a dextran polymer backbone. Sections were then quantified by a clinical pathologist according to good clinical practice guidelines for approved diagnostic PD-L1 quantification.P values < 0.05 were retained as significant. Unless otherwise specified, multivariate Cox regression was used to calculate the hazard of death; fast-backward method was applied to select the covariates retained in the multivariate models . The Akaike Information Criterion [AIC] as a stopping rule was used to select the covariates in the final model in order to weight the probability of both significance and prediction strength. The model performance was quantified with C-indexes, calculated after validation with 200 bootstraps  and compared with analysis of variance. A nomogram (rms R package) was tailored on the final regression model for the melanoma TCGA cohort; the total number of points derived by specifying the covariate values was used to calculate the expected survival probabilities at 24 and 60 months; to proceed with the nomogram design, the missing values in the final regression model were estimated with multiple imputations using additive regression, bootstrapping, and predictive matching; a correction on the estimation procedure was based on 200 multiple imputations. Cox–Snell residuals were used to verify the proportional hazard hypothesis . Kaplan–Meier method with log-rank test was used to plot survival data and patients’ allocation to groups were based on the biomarker cut-off determined with OptimalCutpoints R package, with the exception that the TCR metrics were retained as continuous variables for all the regression analyses to avoid cut-off artifacts and selection bias. Simple logistic regression was applied to calculate the log-likelihood ratio of radiological response to anti-PD1 therapy according to the clonality of baseline biopsy TIL/Tc; the AUC of the ROC was calculated for the parameters sensitivity and 1 − specificity. We used the “rule of the thumb” to determine the maximum number of covariates to use in the regression models22. Samples with less than four TCR sequences were outbound for the algorithm to calculate Renyi index and were excluded from the analysis. TCGA samples with incomplete clinical annotation and no survival information were included in the TCR analysis shown in Fig. All tests were two-sided and Further information on research design is available in the Supplementary InformationPeer Review FileReporting Summary


Additionally, we have tested the utility of long-term archival blood samples from DLBCL patients to detect circulating tumor DNA (ctDNA). We observed a higher cfDNA yield using the QIAamp Circulating Nucleic Acid Kit (Qiagen) purification kit, as well as a higher cfDNA yield when blood samples were collected in EDTA BCTs, with a centrifuge regime at 2000 × g. Moreover, ctDNA detection was feasible from archival plasma samples with a median storage time of nine years.DNA released from cells into the peripheral blood is known as cell-free DNA (cfDNA), representing a promising noninvasive source of biomarkers that could be utilized to manage Diffuse Large B-Cell Lymphoma (DLBCL), among other diseases. The procedure for purification and handling of cfDNA is not yet standardized, and various preanalytical variables may affect the yield and analysis of cfDNA, including the purification kits, blood collection tubes, and centrifugation regime. Therefore, we aimed to investigate the impact of these preanalytical variables on the yield of cfDNA by comparing three different purification kits DNeasy Blood & Tissue Kit (Qiagen), QIAamp Circulating Nucleic Acid Kit (Qiagen), and Quick-cfDNA Serum & Plasma Kit (Zymo Research). Two blood collection tubes (BCTs), EDTA-K2 and Cell-Free DNA (Streck), stored at four different time points before plasma was separated and cfDNA purified, were compared, and for EDTA tubes, two centrifugation regimes at 2000 ×  Diffuse Large B-Cell Lymphoma (DLBCL) accounts for 30–40% of all newly diagnosed non-Hodgkin lymphoma cases . The firThe cfDNA consists mainly of double-stranded DNA fragments with lengths of approximately 180 bp, reflecting the segment of DNA wound around a histone octamer but can also be shorter double-stranded fragments, highly degraded fragments, or partially single-stranded fragments of DNA circulating extracellularly in body fluids . cfDNA iIt has been shown that ctDNA fragments are shorter than normal cfDNA fragments ranging from 90 to 150 bp detected in blood plasma .Detecting ctDNA from blood plasma and serum is challenging as it accounts only for a small fraction (less than 1%) of the total amount of cfDNA, and preanalytical processes including blood collection, purification, and storage are not yet fully standardized . For ctDIn this study, two types of commercial BCTs were evaluated for the ability to prevent cfDNA contamination caused by gDNA release as detected by the Agilent 2100 Bioanalyzer (Agilent Technologies). We have also examined three cfDNA purification kits and the usability of archival matched plasma and tumor tissue biopsies assessed by digital droplet Polymerase Chain Reaction (ddPCR). This study is aimed at guiding optimization of preanalytical cfDNA processing variables, ensuring reliable detection of ctDNA.n = 8) was collected in EDTA and Streck blood collection tubes in agreement with the Health Ethics Committee of Region North Denmark.Peripheral blood from each healthy donor (n = 15) from the Department of Hematology, Aalborg University Hospital, Denmark. Samples were collected at the time of diagnosis (n = 9) or relapse (n = 6) and were all part of research protocols RetroSeq  and ProSeq  approved by the Health Ethics Committee of Region North Denmark. All samples were analyzed by whole-exome sequencing (WES) [n = 6) or within 24 hours (n = 9) after the blood was drawn. The median storage time of tissue biopsies and corresponding plasma samples was nine years, ranging from 9 to 14 years for diagnostic samples and 3 to 9 years for relapsed samples.Paired tumor biopsy and matched blood plasma samples were obtained from DLBCL patients (ng (WES) . Blood sn = 3). Purification of cfDNA using the QIAamp Circulating Nucleic Acid Kit (Qiagen), Quick-cfDNA Serum & Plasma Kit (Zymo Research), and DNeasy Blood & Tissue Kit (Qiagen) was performed following the manufacturer's instructions. cfDNA was eluted in 50 μl elution buffer. Assessment of cfDNA size and yield was performed by Bioanalyzer and Qubit analysis.To examine the impact of purification kits on the yield of cfDNA, three DNA purification kits were compared: DNeasy Blood & Tissue Kit (Qiagen), QIAamp Circulating Nucleic Acid Kit (Qiagen), and Quick-cfDNA Serum & Plasma Kit (Zymo Research). cfDNA was purified from blood samples collected from healthy volunteers  Assay Kit (Thermo Fisher Scientific) followed by storage at −20°C.Purification of gDNA from tumor tissue biopsies was performed using AllPrep DNA/RNA Mini Kit (Qiagen) following the manufacturer's instructions as described previously . Purificn = 6) donated 7 × 10 ml blood in K2 EDTA  BCTs and 4 × 10 ml Cell-Free DNA Streck BCT . Blood samples in Streck BCTs were purified within 30 minutes (fresh plasma) from a blood draw or after storing it at room temperature (RT) for one, four, or 24 hours after a blood draw, followed by plasma separation and freezing at −80°C for one week before purification  (g at RT for 10 minutes (Eppendorf centrifuge); plasma was collected by pipetting and centrifuged at 16000 × g for 10 minutes. Blood samples collected in EDTA BCTs were centrifuged for 10 minutes at 2000 × g or 3000 × g at RT for each storage time. After separation of plasma, for both types of tubes, cfDNA was immediately purified from 1.5 ml aliquots of plasma by the QIAamp Circulating Nucleic Acid Kit (Qiagen) following the manufacturer's instruction. The fragmentation size of cfDNA in blood plasma was examined by a Bioanalyzer, and cfDNA concentration was determined by the Qubit dsDNA High-Sensitivity (HS) Assay Kit (Thermo Fisher Scientific).To investigate the impact of blood collection tubes on cfDNA yield and stability during blood sample storage, each healthy volunteer ( plasma) . For then = 15) by ddPCR, purified plasma samples were eluted in 50 μl elution buffer provided with the QIAamp Circulating Nucleic Acid Kit (Qiagen) and stored at 4°C until ddPCR analysis. Positive control samples containing both wild-type (WT) and mutant (MT) DNA were created for each assay by purifying gDNA from DLBCL cell lines and mixing it with gBlocks purchased from Integrated DNA Technologies (IDT). For each assay, at least three wells with nontemplate controls (NTCs) were used to control environmental contamination, and at least five wells with wild-type controls (WTC) (DLBCL cell lines without the mutation of interest) were used to estimate false-positive rates. The limit of detection was determined for each assay by examining 30-40 wells of cell line gDNA. Reaction volume of 22 μl for ddPCR was prepared by 13 μl master mix (12 μl Supermix for Probes (No dUTP), 1 μl of primer/probe mix for both FAM and HEX) and 9 μl template cfDNA from patient plasma. For NTCs, 9 μl of nuclease-free water was added instead of plasma-purified cfDNA. WTC was generated by adding 9 μl of WT cell line gDNA. The positive controls were generated as ~30% fractional abundance of MT and included in each assay to facilitate thresholding. Wells with total droplet counts of less than 11,000 were considered invalid and were excluded from analysis, ensuring high-quality data. From the PCR mixture, 20 μl was used for droplet generation according to the manufacturer's instructions, and ddPCR was performed using the QX200 ddPCR system (Bio-Rad Laboratories). The QuantaSoft (Bio-Rad Laboratories) software was used for data analysis. For each patient, cfDNA was analyzed in duplicates, and ddPCR results were automatically calculated by the QuantaSoft software based on the mean from estimated target DNA concentrations (copies/μl) in merged wells.To investigate the detection of ctDNA in archived DLBCL clinical samples . Statistical tests performed were a one-way ANOVA test and Wilcoxon signed-rank test.n = 15) to validate the presence of known somatic mutations in tumor tissue and ctDNA.To investigate the effects of preanalytical steps on the quantity of cfDNA in plasma samples, purification kits, blood collection tubes, storage time before processing whole blood, and centrifugation regimen were tested as variables for cfDNA yield and quality. Usability of optimized preanalytical steps was applied on archival tumor tissue and plasma samples (The yield of cfDNA from blood plasma was assessed using three different DNA purification kits: DNeasy Blood & Tissue Kit (Qiagen), QIAamp Circulating Nucleic Acid Kit (Qiagen), and Quick-cfDNA Serum & Plasma Kit (Zymo Research). cfDNA was purified from blood samples drawn from three healthy volunteers who simultaneously had 3 × 10 ml peripheral blood drawn for each purification kit, and cfDNA was purified from plasma in duplicates. The yield of purified cfDNA was significantly higher from all three volunteers when using the QIAamp Circulating Nucleic Acid Kit compared to the Quick-cfDNA Serum & Plasma Kit and DNeasy Blood & Tissue Kit . The Quin = 6) and stored the samples at various conditions before plasma processing  and Streck BCTs , the individual yield of purified cfDNA was determined. For majority of individuals, the total cfDNA yields in EDTA BCTs were slightly increased compared to Streck BCTs at different time points with mean values ranging from 18 to 83 ng/50 μl for EDTA and 11-28 ng/50 μl for Streck, respectively (g) as compared to Streck BCTs ), 15 plasma samples from patients with DLBCL were purified using the QIAamp Circulating Nucleic Acid Kit (Qiagen). We have used ddPCR to investigate if it is possible to detect previously identified mutations from tumor tissue samples in ctDNA from the same patients. The mutations were identified by WES in the EZH2, CD58, and TNFRSF14 genes. All positive tumor tissue samples were positive in the ddPCR analysis of cfDNA when the plasma was extracted from EDTA BCTs and centrifuged by 2000 × g  performed the most efficiently with a significantly increased yield of cfDNA compared to the two other kits investigated, while all three kits performed well in terms of assessed fragmentation size of cfDNA Figure . The QIAg and 3000 × g) with a consistent slight increase in cfDNA yield at 2000 × g becoming more pronounced over time. Therefore, we suggest EDTA BCTs for blood collection if the blood samples can be processed within 24 h and a relative centrifugation force of 2000 × g for an optimal yield of cfDNA.To assess the yield of cfDNA and blood stabilizing capability when using different BCTs, blood samples from six healthy volunteers were stored parallel in two different BCTs for different periods of time and temperatures before plasma was separated. The two types of commercially used BCTs showed similar performance in preserving cfDNA when plasma was freshly processed and when blood was stored for 1 h and 4 h before plasma separation and freezing for one week, followed by cfDNA purification. This observation is in line with the literature where studies recommend processing blood samples drawn in EDTA BCTs immediately or up to two hours from the blood drawn to circumvent the short half-life of cfDNA and contamination by gDNA –27. NeveCD58, TNFRSF14, and EZH2 genes using mutation-specific ddPCR assays. The archival blood samples were collected in EDTA BCTs (centrifuged at 2000 × g for 10 minutes) and stored in N2(I) for a median of nine years. The presence of specific somatic mutations in ctDNA matching tumor gDNA was confirmed, but fractional abundance was decreased compared to gDNA. This was expected due to the dilution of ctDNA in total cfDNA and for our samples, which have been stored in liquid nitrogen for as much as 14 years (average 8.4 years). A recent study has shown that storage of processed plasma up to one year at −80°C does not degrade cfDNA, whereas longer storage results in 30% of degradation per year [To assess archival plasma samples usability from our biobank, we investigated the presence of ctDNA in archival samples with known rare point mutations in the per year . HoweverIn conclusion, our results suggest that QIAamp Circulating Nucleic Acid Kit (Qiagen) as a reliable kit for purification of cfDNA and that blood samples, for which plasma cannot be separated within four hours or stored at 4°C, should be collected in Streck BCTs that can keep cfDNA stable for up to 14 days before processing , 27. Als


Many viruses involved in interference are pathogenic to humans or to economically important animals. Thus the phenomenon may be relevant to medicine and to animal production due to the possibility to use it as alternative to chemical therapies against virus infections to reduce the severity of disease/mortality caused by a superinfecting virus. Virus interference is defined as the host resistance to a superinfection caused by a pathogenic virus causing obvious signs of disease and/or mortality due to the action of an interfering virus abrogating the replication of the former virus. Different degrees of inhibition of the superinfecting virus can occur. Due to the emergence of novel pathogenic viruses in recent years, virus interference has recently been revisited using different pathogens and hosts, including commercially important farmed aquatic species. Here, some highly pathogenic viruses affecting farmed crustaceans can be affected by interference with other viruses. This review presents data on the history of virus interference in hosts including bacteria and animals, with emphasis on the known cases of virus interference in crustacean hosts.Virus interference is a phenomenon in which two viruses interact within a host, affecting the outcome of infection of at least one of such viruses. The effect of this event was first observed in the XVIII century and it was first recorded even before virology was recognized as a distinct science from microbiology. Studies on virus interference were mostly done in the decades between 1930 and 1960 in viruses infecting bacteria and different vertebrates. The systems included Life Science Identifiers (LSIDs)Escherichia coli [(Migula 1895) Castellani & Chalmers 1919]Aedes albopictus (Skuse 1894)Liocarcinus depurator (Linnaeus 1758): urn:lsid:marinespecies.org:taxname:107387Penaeus duorarum (Burkenroad 1939): urn:lsid:marinespecies.org:taxname:158334Carcinus maenas (Linnaeus 1758): urn:lsid:marinespecies.org:taxname:107381Macrobrachium rosenbergii (De Man 1879): urn:lsid:marinespecies.org:taxname:220137Penaeus vannamei (Boone 1931): urn:lsid:zoobank.org:pub:C30A0A50-E309-4E24-851D-01CF94D97F23Penaeus monodon (Fabricius 1798): urn:lsid:zoobank.org:act:3DD50D8B-01C2-48A7-B80D-9D9DD2E6F7ADPenaeus stylirostris (Stimpson 1874): urn:lsid:marinespecies.org:taxname:584982 Virus interference is a phenomenon observed before the dawn of virology itself and even before proper experimental methods were available in the decade of 1950 . The earEscherichia coli [(Migula 1895) Castellani & Chalmers 1919], was used as host upon which two distinct bacteriophage strains , were able to replicate. The interference experiments showed that using equal amounts of these two viruses (α and γ), virus γ inhibited replication of virus α by 67%. Also, the interference did not occur by differences in virus adsorption by the cells, and the time at which virus γ was inoculated after virus α influenced the interference, with longer times (4 - 6 min) showing less interference  and other cytokines, cellular immune responses or immunostimulation  C6/36 cell cultures  simultaneously infected with two different types of T bacteriophages showed interference, as one single interfering virus particle was able to inhibit replication of a super-infective virus in any bacterial cell . Bacteria  the interference was not due to differences in virus adsorption to cells, penetration into the host cell or competition for a key enzyme , 18, 23;Examples of superinfection exclusion in animal hosts include various homologous interfering viruses such as influenza virus , 23, visThe interference of homologous viruses is far more difficult to distinguish from the immunological effects and genetic interactions than for heterologous interference, since both the interfering and superinfecting viruses are antigenically equivalent . Nonethein vivo or in vitro. Another criterion for heterologous virus interference is the lack of immunogenicity against the virus pairs by the host, or the independence of interference to any relationship to antigenic reactions and antibody production. This type of interference has been reported among viruses that are antigenically and taxonomically distinct  and hemagglutinating (HA) antigens produces broadly cross-reacting neutralizing antibodies . NonetheThis interaction is another example of the category of direct interactions of viral genes or gene products. This occurs in any virus that may lack replication ability at some degree and hence requires the gene products of another virus to produce infection. This interaction does not produce virus interference, but it allows a defective virus to successfully replicate and exit the cell. An example of this interaction occurs in the bacteriophage P4, which is able to replicate its own genome in the presence of a coinfecting phage (P2), thus providing capsid components and cell lysis .In vertebrates, an adeno-associated virus (AAV) is a replication-defective parvovirus that usually requires a host cell that is coinfected with an adenovirus or herpesvirus in order to produce virions to be released from the host cell. Later, it was discovered that AAV is not completely replication defective, since genotoxic stress and other factors may also make a host cell permissive for AAV progeny production .Macrobrachium rosenbergii (De Man 1879) causing muscle whitening in the abdomen and sometimes cephalothorax, resulting in massive mortalities to postlarvae (Macrobrachium rosenbergii Nodavirus (MrNV) is icosaedrical with 27 nm diameter and its genome composed by two equimolar linear single-stranded (ss) RNA molecules of ≈ 3200 and 1250 nucleotides, respectively  (Penaeus duorarum (Burkenroad 1939), the virus Baculovirus penaei  . Later, s penaei  was firss penaei , 47. Sins penaei . At press penaei . Crustacs penaei . Severals penaei , 37, 50 Carcinus maenas (Linnaeus 1758) was first mentioned in 1971 and later found to display autointeference in the same host (-2 and 10-3) did. This effect is similar to the phenomenon of autointerference observed in vertebrates. Autointerference was tested with undiluted and diluted hemolymph samples and it was observed when the more diluted samples caused disease faster than the undiluted ones. All six samples of whole hemolymph taken late in the course of disease did not show the normal dilution effect or even showed a reversal. Further, none of the fresh sera samples taken showed the expected normal dilution effect, and five out of six (83%) showed autointerference. This phenomenon could not be determined to be caused by the virus, from an associated virus or by the innate defense system  and the black tiger shrimp Penaeus monodon (Fabricius 1798) among others (Marine shrimp is an important commodity and is produced in aquaculture facilities in many countries worldwide. The main farmed species are the Pacific white shrimp g others . Many vig others . Due to Taura syndrome virus (TSV) has a single stranded, positive-sense linear RNA genome and replicates in cytoplasm (Yellow-head virus (YHV) has a single-stranded positive sense RNA genome and also replicates in cytoplasm  of YHV. Results showed that virus interference occurred between TSV and YHV and survival of shrimp treated with TSV was significantly higher than YHV positive controls at the different times evaluated. The highest survival occurred when YHV was inoculated at 27 d after TSV inoculation  (Penstylhamaparvovirus 1 (white spot syndrome virus 1 (WSSV) (Penaeus stylirostris (Stimpson 1874) and disease to P. vannamei and P. monodon (Probably the most studied virus interference event in shrimp is between  (IHHNV) , also knovirus 1 , and whi1 (WSSV) . The IHH1 (WSSV) . This vi1 (WSSV) . It caus monodon . The WSS monodon . WSSV isP. stylirostris , whereas moribund and dead shrimp had higher WSSV load than IHHNV (107 vs 104), respectively. The protective effect of IHHNV infection lasted at least 6 weeks.The first evidence of interference was found in experiments done in juvenile Pacific blue shrimp irostris . Shrimp P. vannamei postlarvae. Shrimp treated with IHHNV at nauplius V or zoea I stages or treated with formalin-inactivated WSSV showed a delay in shrimp mortality from day 4 until the end of the experiment, indicating an interfering effect of such treatments. Nonetheless, shrimp treated with IHHNV or inactivated WSSV had 4 and 4.7% survival at 10 d post WSSV challenge, respectively. Surviving shrimp had similar virus loads between IHHNV and WSSV , whereas moribund shrimp had higher WSSV load   .per os in juvenile P. vannamei was evaluated at different times after IHHNV inoculation (0 to 50 d). Shrimp challenged only with WSSV died at 3 dpi, whereas shrimp treated with IHHNV between 30 and 50 d before WSSV challenge died at 5 dpi. The virus load in shrimp treated with IHHNV showed an increase during the 50 d peaking at 40 d with an average IHHNV virus load of 2.6 × 109 copies μg–1 DNA. Shrimp challenged with WSSV showed a reduction in IHHNV load (2.7 × 107 and 9.7 × 107 copies μg–1 DNA) compared to shrimp inoculated only with IHHNV (2.5 × 108 - 2.6 × 109 copies μg–1 DNA) at 30 and 40 d, respectively. A delay in mortality due to WSSV infection was a function of IHHNV virus load and duration of infection. A significant delay in mortality occurred when IHHNV load was higher than 108 copies μg–1 DNA at the time of WSSV challenge . This method requires the analysis of DNA/RNA obtained from the environment or organisms, including soil, water, host tissues, feces and other samples. Two common eDNA methods are amplicon-based (metabarcoding) or whole shotgun metagenomics/metatranscriptomics. The former amplifies and sequences variable regions of conserved genes  or mitochondrial intergenic regions that are shared across a group or sub-groups of a selected organism. The diversity of the resulting sequences are used to assign operational taxonomic units (OTUs). In the case of viruses which lack these conserved regions, the latter method is used to study viral communities in environmental samples .In conclusion, virus interference is an old phenomenon that implies the interaction of two viruses within a host cell, resulting in the inhibition of replication of at least one of the viruses. This phenomenon may have various mechanisms, of which three have been reported. The exclusion interference may be common in viruses infecting animals. Heterologous virus interference between a low and a highly pathogenic viruses has been reported in farmed shrimp and it could be used as a natural control strategy against highly pathogenic viruses. As sequencing technology advances, better knowledge on environmental and crustacean virus diversity will be gained, and also in virus genome organization and gene interactions between host - pathogen and virus - virus interactions, may help elucidate the mechanisms that drive this phenomenon.The author confirms being the sole contributor of this work and has approved it for publication.The present work was supported by Instituto Politecnico Nacional projects SIP20200533 and SIP20210092. COFAA-IPN provided financial support to publish this article.The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.