Biology subjects

Tong, S.

Publications and source records attributed to Tong, S..

At least 19 recordsLinked to original sources

bioRxiv2026

AutoScreen: AI Co-Scientist System for Target Discovery in Functional Genomics

Target discovery in functional genomics remains largely manual and time-consuming, lacking systematic tools for efficient and reproducible gene-level hypothesis generation. We introduce AutoScreen, an AI co-scientist system supporting target discovery through both Pre-screen Design, which constructs perturbation libraries de novo from free-text research descriptions, and Post-screen Analysis, which re-ranks experimental screen hits by integrating statistical scores with biological context. AutoScreen leverages the complementary strengths of multiple specialist agents that perform deep research into multi-modal evidence, information restructuring, parallel searches across >26 biomedical databases, evidence synthesis, and target review to provide transparent, explainable gene prioritization with pipeline provenance. Across 320 genome-scale CRISPR screens as expert-curated benchmarks, AutoScreen achieved a ~19% increase in validated-hit recovery among its top 100 predictions, relative to the strongest agent baseline, and required a 1.2-fold smaller library to recover the same number of hits at the top-500 reference point. AutoScreen reached mean average precision more than two orders-of-magnitude above random baseline. Further, we validated AutoScreen in cancer immune-evasion case studies focusing on natural killer (NK) and T-cell therapeutics. AutoScreen recovered NK-resistance genes that were initially lower-ranked in a leukemia screen, moving MUC1, PDPN, and LRRC15 from raw ranks of 118, 81, 1384 to 5, 44, 659, respectively. In follow-up tumor killing assay with primary human NK cells, individual perturbation validated all three hits successfully. Next, in prospective benchmarking across two cytotoxic T-cell-killing screens, AutoScreen recovered 77.1% of ground-truth hits called by the consensus of two gold-standard analysis pipelines (FDR<0.1), achieving 8% improvement over the strongest general-purpose LLM agent baseline. Finally, we re-analyzed >500 public datasets to construct the AutoScreen Resource Hub, a growing knowledge base of pre-computed, annotated reports for CRISPR screens, RNA-seq differential expression, and gene-level UK Biobank genome-wide association studies. This agentic AI approach enables real-time genomics benchmark construction that are continuously updated, expanded, for evaluating frontier AI co-scientists. Overall, AutoScreen enables AI-powered target discovery to be more auditable, scalable, extensible, and reproducible.

bioengineering↗

bioRxiv2026

Loss of GdpP function in Staphylococcus aureus confers β-lactam-specific antibiotic tolerance and promotes invasive infection

The emergence of antibiotic tolerance in Staphylococcus aureus reduces antibiotic efficacy by allowing bacterial survival despite prolonged antibiotic exposure, the molecular basis of which remains poorly understood. Moreover, the phenotypic indistinguishability of tolerant isolates in antimicrobial susceptibility testing impedes effective diagnosis and therapy. Increased concentration of the second-messenger, cyclic-di-AMP (CDA), has recently been implicated in tolerance to {beta}-lactams as well as other cell-wall-reactive antibiotics. Using the ScanLag assay, Tolerance-Disk test, and traditional methodologies and employing isogenic mutagenized strains, we demonstrate that loss of GdpP function, a phosphodiesterase that hydrolyzes CDA, confers tolerance specifically to {beta}-lactam antibiotics independent of their class. The extent of {beta}-lactam tolerance correlated directly with the intracellular CDA concentration and inversely with the inhibition of bacterial cell-wall synthesis. {Delta}gdpP mutants caused higher mortality than wild-type strains in the Galleria mellonella infection model upon {beta}-lactam treatment, suggesting GdpP-mediated tolerance could lead to {beta}-lactam treatment failure. Large-scale within-host evolution analysis demonstrated that MRSA and MSSA strains isolated from patients acquire GdpP loss-of-function mutations during invasive infections but not during nasal carriage. Overall, this study highlights the clinical relevance of gdpP mutations, frequently selected in persistent S. aureus infections, as key mediators that could promote treatment failure due to {beta}-lactam tolerance.

microbiology↗

bioRxiv2026

Physical laws predict methane hotspots in global mountain waters

Accurate accounting of aquatic methane emissions is critical for climate change mitigation, yet current global budgets overlook a key driver: the elevation-regulated atmospheric pressure. Here, we present the first large-scale investigation of methane ebullition across 164 shallow waters spanning elevations from sea level to 4886 meters. We demonstrate that ebullition rate increases with elevation-over four times higher at >3000 m a.s.l. than at sea level-due to two synergistic, pressure-dependent physical mechanisms: a degas effect (enhanced bubble formation) and a trigger effect (facilitated bubble ascent). Independent theoretical prediction of the combined effects shows near-perfect agreement with the empirical elevation trend, quantitatively confirming that these physical mechanisms are the primary drivers of enhanced ebullition at high elevations. Our findings reveal that mountain aquatic ecosystems represent unaccounted methane hotspots that have been systematically underestimated in global inventories.We therefore call for urgent integration of these ecosystems into IPCC assessments and targeted mountain mitigation and sustainable management strategies.

ecology↗

bioRxiv2026

Multi-Modal Deep Learning Integrates Spatial Topologies and Sequential Motifs to Identify Class I HDAC Inhibitors as Pan-Cancer Therapeutics

The molecular characterization of human solid tumors has introduced immense genomic complexity and intra-tumoral diversification. Converting these detailed, multi-omic profiles right into workable, broad-spectrum therapeutics continues to be an formidable bottleneck in precision oncology. Traditional computational drug repurposing strategies largely rely on single-modality chemical descriptors, which frequently fail to capture the systemic transcriptomic interactions within the highly dynamic tumor microenvironment. Here, this study presents a robust multi-modal deep learning framework that synergistically integrates two-dimensional (2D) molecular graphs via Graph Neural Networks (GNNs) and chemical functional group patterns via self-attention Transformers. By mapping this dual-stream chemical feature space to the perturbational transcriptomic signatures (LINCS L1000) of 22 distinct cancer types from The Cancer Genome Atlas (TCGA), a vast library of over 28,000 small-molecule compounds was computationally screened. The developed multi-modal architecture achieved state-of-the-art predictive accuracy, significantly outperforming traditional single-modality baseline models. Strikingly, the comprehensive pan-cancer transcriptomic reversal landscape identified a persistent convergence of non-oncology drugs exhibiting potent broad-spectrum anti-tumor potential. Specifically, Class I Histone Deacetylase (HDAC) inhibitorsmost notably TC-H-106, RG2833, and Tianeptinaline, agents originally developed to penetrate the blood-brain barrier for neurodegenerative and psychiatric disordersemerged as top therapeutic candidates across lung adenocarcinoma (LUAD), bladder urothelial carcinoma (BLCA), and rectum adenocarcinoma (READ). Subsequent high-dimensional network pharmacology and functional enrichment analyses confirmed that these agents robustly suppress essential oncogenic pathways, specifically collapsing the G1/S phase transition and DNA damage repair machineries. Furthermore, structural validation via molecular docking and force-field thermodynamics confirmed the highly stable physical binding affinity (Vina score: -7.0 kcal/mol, MMFF94 Energy: 64.76 kcal/mol) of TC-H-106 to the HDAC1 catalytic pocket. Kaplan-Meier survival analysis based on TCGA gene expression stratification underscored the significant prognostic benefit of targeting this epigenetic axis. Collectively, these findings introduce a powerful multi-modal AI framework for systems-level drug repurposing and highlight brain-penetrant Class I HDAC inhibitors as highly promising candidates for pan-cancer epigenetic therapy.

bioinformatics↗

bioRxiv2026

Defining influenza-specific B cells in vaccine responders, non-responders and influenza breakthrough infections

Although seasonal influenza vaccination programs are effective at a population level, our data from inactivated influenza vaccine (IIV) cohorts in years 2015-2022 reveal that 50-60% of individuals do not seroconvert following immunization. The underlying mechanisms of vaccine non-responsiveness are far from understood. In this study, we sought to define key determinants of optimal B cell immune responses elicited by seasonal influenza vaccination, and to explore why some individuals fail to elicit humoral immunity following immunization. Immune responses associated with seroconversion and vaccine failure from individuals immunized with IIVs were compared at cellular and molecular levels using single-cell transcriptomics. We analyzed HA-specific B cell immunity across vaccine-responders, breakthrough infections and patients hospitalized with acute influenza. Droplet-based single-cell RNA sequencing and VDJ-sequencing of influenza-specific B cells from stored PBMCs was performed using 10x Genomics. Our results show that atypical B cells are the major subset of B cell responses in vaccine non-responders on day 28 post-vaccination. Conversely, individuals who seroconvert had diverse B cell phenotypes. The use of recombinant influenza-specific HA probes allowed us to dissect expression patterns on influenza HA-specific B cells. We found that HA-specific B cells of vaccine non-responders for A/H1N1 and A/H3N2 components displayed elevated atypical-like markers (CD11c, FcRL-5) at baseline, compared to responders. Analysis of differentially expressed genes (DEGs) between responders and non-responders identified differential expression of HLA-DR, CD74, CD83, and CXCR3 genes. We subsequently demonstrated reduced frequencies of HLA-DR-, CD74- and CD83-expressing B cells in patients hospitalized with influenza, compared to healthy participants. Hospitalized influenza patients also had significantly higher proportions of atypical CD21-CD27- B cells. Overall, our data demonstrate an association between elevated frequencies of atypical-like B cells with both lack of seroconversion following immunization and severe influenza infection. These findings broaden our understanding of humoral immunity in influenza vaccination and infection, providing novel insights for vaccination strategies and design.

immunology↗

bioRxiv2026

Magnetically activatable insect viral vectors promote anticancer immunity through spatially confined gene disruption

Precise control of genome editing activity in vivo remains a major barrier to the clinical translation of CRISPR-based therapeutics, as current approaches cannot reliably restrict editing activity to target tissues 1,2,3. Here we show that a magnetically gated baculoviral CRISPR platform enables spatial control of genome editing activity 4. By coupling magnetic activation of viral transduction at target sites with complement-mediated inactivation of circulating vectors, this system functionally confines genome editing activity to defined spatial contexts, effectively decoupling editing activity from biodistribution. We further show that spatially confined genome editing can be coupled with endogenous antiviral sensing to drive coordinated immune modulation within tumours. In a syngeneic murine tumour model, local administration combined with magnetic activation restricts genome editing to tumours without detectable editing in major organs, remodels dendritic cell and CD8{square} T cell states, suppresses tumour growth, and extends survival. Together, these findings establish a generalizable strategy for spatial control of genome editing and localized immunomodulation in cancer.

bioengineering↗

bioRxiv2025

Tonic pain revalues associative memories of phasic pain

Tonic pain is proposed to adapt protective behaviours during recovery from injury. A key untested prediction of this homeostatic model is that it appropriately reshapes internal representations of phasic pain. We investigated whether lateralised tonic pain modulates phasic pain-predictive cues on that side. Using a virtual-reality Pavlovian revaluation paradigm, we assessed physiological and neural conditioned responses with EEG in theta, alpha, and beta frequency bands. Pain-predictive cues elicited neural enhanced alpha and beta suppression and increased pupil diameter during conditioning acquisition. Critically, tonic pain revalued phasic conditioned responses during extinction, with reduced midfrontal theta synchronisation when the laterality of tonic pain was congruent with predicted phasic pain. Greater tonic pain unpleasantness also enhanced posterior beta suppression for congruent cues. These findings provide evidence for an internal representation of cue-pain associations that is topographically modulated by tonic pain, suggesting that tonic pain actively reconfigures pain predictions, enabling anticipatory protective behaviours.

neuroscience↗

bioRxiv2025

Phasic and tonic pain serve distinct functions during adaptive behaviour

Pain drives self-protective behaviour, and evolutionary theories suggest it acts over different timescales to serve distinct functions. Whilst phasic pain provides a teaching signal to drive avoidance of new injury, tonic pain is argued to support recuperative behaviour, for instance by reducing motivational vigour. We test this hypothesis in an immersive virtual reality EEG foraging task where subjects harvested fruit in a forest: some fruit elicited brief phasic pain to the grasping hand, and this reduced choice probability. Simultaneously, tonic pressure pain to the contralateral upper arm was associated with reduced action velocities. This could be explained by a free-operant computational framework that formalises and quantifies the function of tonic and phasic pain in terms of motivational vigour and decision value, and model parameters correlated with physiological and neural responses. Overall, the results show how tonic and phasic pain subserve distinct objective motivational functions that support harm minimisation during ongoing adaptive behaviour.

neuroscience↗

bioRxiv2024

Balancing safety and efficiency in human decision making

The safety-efficiency dilemma describes the problem of maintaining safety during efficient exploration and is a special case of the exploration-exploitation dilemma in the face of potential dangers. Conventional exploration-exploitation solutions collapse punishment and reward into a single feedback signal, whereby early losses can be overcome by later gains. However, the brain has a separate system for Pavlovian fear learning, suggesting a possible computational advantage to maintaining a specific fear memory during exploratory decision-making. In a series of simulations, we show this promotes safe but efficient learning and is optimised by arbitrating Pavlovian avoidance of instrumental decision-making according to uncertainty. We provide a basic test of this model in a simple human approach-withdrawal experiment in virtual reality, and show that this flexible avoidance model captures choice and reaction times. These results show that the Pavlovian fear system has a more sophisticated role in decision-making than previously thought, by shaping flexible exploratory behaviour in a computationally precise manner.

neuroscience↗

bioRxiv2023

Magnetic nanocomplexes coupled with an external magnetic field modulate macrophage phenotype: a non-invasive strategy for bone regeneration.

Chronic inflammation is a major cause for the pathogenesis of musculoskeletal diseases such as fragility fracture, and nonunion. Studies have shown that modulating the immune phenotype of macrophages from proinflammatory to prohealing mode can heal recalcitrant bone defects. Current therapeutic strategies predominantly apply biochemical cues, which often lack target specificity and controlling their release kinetics in vivo is challenging spatially and temporally. We show a magnetic iron-oxide nanocomplexes (MNC)-based strategy to resolve chronic inflammation in the context of promoting fracture healing. MNC internalized pro-inflammatory macrophages, when coupled with an external magnetic field, exert an intracellular magnetic force on the cytoskeleton, which promotes a prohealing phenotype switch. Mechanistically, the intracellular magnetic force perturbs actin polymerization, thereby significantly reducing nuclear to cytoplasm redistribution of MRTF-A and HDAC3, major drivers of inflammatory and osteogenic gene expressions. This significantly reduces Nos2 gene expression and subsequently downregulates the inflammatory response, as confirmed by quantitative PCR analysis. These findings are a proof of concept to develop MNC-based resolution-centric therapeutic intervention to direct macrophage phenotype and function towards healing and can be translated either to supplement or replace the currently used anti-inflammatory therapies for fracture healing.

bioengineering↗

bioRxiv2023

GluK2 is a target for gene therapy in drug-resistant Temporal Lobe Epilepsy

ObjectiveTemporal lobe epilepsy (TLE) is characterized by recurrent seizures generated in the limbic system, particularly in the hippocampus. In TLE, recurrent mossy fiber sprouting from dentate gyrus granule cells (DGCs) creates an aberrant epileptogenic network between DGCs which operates via ectopically expressed GluK2/GluK5-containing kainate receptors (KARs). TLE patients are often resistant to anti-seizure medications and suffer significant comorbidities; hence there is an urgent need for novel therapies. Previously we have shown that GluK2 knockout mice are protected from seizures. This study aims at providing evidence that downregulating KARs in the hippocampus using gene therapy reduces chronic epileptic discharges in TLE. MethodsWe combined molecular biology and electrophysiology in rodent models of TLE and in hippocampal slices surgically resected from patients with drug-resistant TLE. ResultsHere we confirmed the translational potential of KAR suppression using a non-selective KAR antagonist that markedly attenuated Interictal-like Epileptiform Discharges (IEDs) in TLE patient-derived hippocampal slices. An adeno-associated virus (AAV) serotype-9 vector expressing anti-grik2 miRNA was designed to specifically downregulate GluK2 expression. Direct delivery of AAV9-anti grik2 miRNA into the hippocampus of TLE mice led to a marked reduction in seizure activity. Transduction of TLE patient hippocampal slices reduced levels of GluK2 protein and, most importantly, significantly reduced IEDs. InterpretationOur gene silencing strategy to knock down aberrant GluK2 expression demonstrates inhibition of chronic seizure in a mouse TLE model and IEDs in cultured slices derived from TLE patients. These results provide proof-of-concept for a gene therapy approach targeting GluK2 KARs for drug-resistant TLE patients.

neuroscience↗

bioRxiv2022

MvPPT: a highly efficient and sensitive pathogenicity prediction tool for missense variants

Next generation sequencing technologies both boost the discovery of variants in the human genome and exacerbate the challenges of pathogenic variant identification. In this study, we developed mvPPT (Pathogenicity Prediction Tool for missense variants), a highly sensitive and accurate missense variant classifier based on gradient boosting. MvPPT adopts high-confidence training sets with a wide spectrum of variant profiles, and extracts three categories of features, including scores from existing prediction tools, allele, amino acid and genotype frequencies, and genomic context. Compared with established predictors, mvPPT achieved superior performance in all test sets, regardless of data source. In addition, our study also provides guidance for training set and feature selection strategies, as well as reveals highly relevant features, which may further provide biological insights of variant pathogenicity.

bioinformatics↗

bioRxiv2021

Differential neutralization and inhibition of SARS-CoV-2 variants by antibodies elicited by COVID-19 mRNA vaccines

IntroductoryThe evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in the emergence of many new variant lineages that have exacerbated the COVID-19 pandemic. Some of those variants were designated as variants of concern/interest (VOC/VOI) by national or international authorities based on many factors including their potential impact on vaccines. To ascertain and rank the risk of VOCs and VOIs, we analyzed their ability to escape from vaccine-induced antibodies. The variants showed differential reductions in neutralization and replication titers by post-vaccination sera. Although the Omicron variant showed the most escape from neutralization, sera collected after a third dose of vaccine (booster sera) retained moderate neutralizing activity against that variant. Therefore, vaccination remains the most effective strategy to combat the COVID-19 pandemic.

microbiology↗

bioRxiv2021

Mining bacterial NGS data vastly expands the complete genomes of temperate phages

Temperate phages (active prophages induced from bacteria) help control pathogenicity, modulate community structure, and maintain gut homeostasis1. Complete phage genome sequences are indispensable for understanding phage biology. Traditional plaque techniques are inapplicable to temperate phages due to the lysogenicity of these phages, which curb the identification and characterization of temperate phages. Existing in silico tools for prophage prediction usually fail to detect accurate and complete temperate phage genomes2-5. In this study, by a novel computational method mining both the integrated active prophages and their spontaneously induced forms (temperate phages), we obtained 192,326 complete temperate phage genomes from bacterial next-generation sequencing (NGS) data, hence expanded the existing number of complete temperate phage genomes by more than 100-fold. The reliability of our method was validated by wet-lab experiments. The experiments demonstrated that our method can accurately determine the complete genome sequences of the temperate phages, with exact flanking sites (attP and attB sites), outperforming other state-of-the-art prophage prediction methods. Our analysis indicates that temperate phages are likely to function in the evolution of microbes by 1) cross-infecting different bacterial host species; 2) transferring antibiotic resistance and virulence genes; and 3) interacting with hosts through restriction-modification and CRISPR/anti-CRISPR systems. This work provides a comprehensive complete temperate phage genome database and relevant information, which can serve as a valuable resource for phage research.

bioinformatics↗

bioRxiv2021

Of Rats and Men, a Translational Model to Understand Vancomycin Pharmacokinetic/Toxicodynamic relationships

BackgroundVancomycin is a first line antibiotic for many common infectious diseases and is the most commonly prescribed antibiotic in the United States hospital setting. Vancomycin is also well known to cause kidney injury; two recent prospective studies have identified that increasing vancomycin area under the concentration curve predicts vancomycin induced kidney injury (VIKI). However, outside of clinical trials, it is unclear if pre-clinical data can quantitatively describe VIKI in patients. MethodsData were simultaneously analyzed from a pre-clinical rat model and two prospective clinical studies. Logged vancomycin area under the concentration curve (AUC) data for rats (n=48) and patients from PROVIDE (n=263) and CAMERA2 (n=291) were included. VIKI was defined as urinary KIM-1 concentrations [≥]9.42 ng/mL in the rat and according to KDIGO stage 1 kidney injury for all human patients. Multiple generalized linear models were explored, and the order of magnitude was calculated between the probability of acute kidney injury (AKI) from the average obtained in the clinical studies (i.e. CAMERA2 and PROVIDE) and the rat for 0.1 increments in Log10AUC bounded common concentrations obtained in the therapeutic range (i.e. ~200 -800 mg*24h/L). ResultsA logit link model best fit the data. When calculating the multiplicative factors between the studies therapeutic range AUCs, the rat was an average 2.7 to 4.2 times more sensitive to AKI between AUCs of 199.5 (i.e. log 10 AUC=2.3) and 794.3 mg*h/L (i.e. log 10 AUC=2.9), respectively. ConclusionsA pre-clinical rat model was quantitatively linked to toxicity data from two large human studies. The rat is an attractive pre-clinical model to explore exposure toxicity relationships with vancomycin. External validation is required.

pharmacology and toxicology↗

bioRxiv2021

One Health Investigation of SARS-CoV-2 Infection and Seropositivity among Pets in Households with Confirmed Human COVID-19 Cases - Utah and Wisconsin, 2020

BackgroundApproximately 67% of U.S. households have pets. Limited data are available on SARS-CoV-2 in pets. We assessed SARS-CoV-2 infection in pet cohabitants as a sub-study of an ongoing COVID-19 household transmission investigation. MethodsMammalian pets from households with [≥]1 person with laboratory-confirmed COVID-19 were eligible for inclusion from April-May 2020. Demographic/exposure information, oropharyngeal, nasal, rectal, and fur swabs, feces, and blood were collected from enrolled pets and tested by rRT-PCR and virus neutralization assays. FindingsWe enrolled 37 dogs and 19 cats from 34 of 41 eligible households. All oropharyngeal, nasal, and rectal swabs tested negative by rRT-PCR; one dogs fur swabs (2%) tested positive by rRT-PCR at the first animal sampling. Among 47 pets with serological results from 30 households, eight (17%) pets (4 dogs, 4 cats) from 6 (20%) households had detectable SARS-CoV-2 neutralizing antibodies. In households with a seropositive pet, the proportion of people with laboratory-confirmed COVID-19 was greater (median 79%; range: 40-100%) compared to households with no seropositive pet (median 37%; range: 13-100%) (p=0.01). Thirty-three pets with serologic results had frequent daily contact ([≥]1 hour) with the human index patient before the persons COVID-19 diagnosis. Of these 33 pets, 14 (42%) had decreased contact with the human index patient after diagnosis and none (0%) were seropositive; of the 19 (58%) pets with continued contact, 4 (21%) were seropositive. InterpretationsSeropositive pets likely acquired infection from humans, which may occur more frequently than previously recognized. People with COVID-19 should restrict contact with animals. FundingCenters for Disease Control and Prevention, U.S. Department of Agriculture

microbiology↗

bioRxiv2021

Surface-aerosol stability and pathogenicity of diverse MERS-CoV strains from 2012 - 2018

Middle East Respiratory Syndrome coronavirus (MERS-CoV) is a coronavirus that infects both humans and dromedary camels and is responsible for an ongoing outbreak of severe respiratory illness in humans in the Middle East. While some mutations found in camel-derived MERS-CoV strains have been characterized, the majority of natural variation found across MERS-CoV isolates remains unstudied. Here we report on the environmental stability, replication kinetics and pathogenicity of several diverse isolates of MERS-CoV as well as SARS-CoV-2 to serve as a basis of comparison with other stability studies. While most of the MERS-CoV isolates exhibited similar stability and pathogenicity in our experiments, the camel derived isolate, C/KSA/13, exhibited reduced surface stability while another camel isolate, C/BF/15, had reduced pathogenicity in a small animal model. These results suggest that while betacoronaviruses may have similar environmental stability profiles, individual variation can influence this phenotype, underscoring the importance of continual, global viral surveillance.

microbiology↗

bioRxiv2020

Broad-Range Virus Detection and Discovery Using Microfluidic PCR Coupled with High-throughput Sequencing

There is a need for a comprehensive and sensitive method to test for a broad range of viral pathogens in samples without any identifiable pathogen detected. Real-time PCR assays are sensitive and rapid, but their specificity limits their utility in detecting divergent agents. Shotgun high-throughput sequencing methods provide unbiased sequence identification, however, they have limited sensitivity and require complex analyses. In order to meet the need for a sensitive, high-throughput virus detection and discovery platform with good sensitivity, we combine two existing technologies, broadly-reactive consensus-degenerate pan-viral group PCR and the MiSeq sequencer (Illumina), using the Access Array (Fluidigm), a commercially-available microfluidic PCR system. Pan-viral group primers target conserved regions of virus taxonomic groups and can amplify known and potentially novel species. The Access Array employs dozens of these assays in parallel, which are then sequenced all at once on the MiSeq. In this study, we run a respiratory panel of pan-viral group PCR assays using AA-PCR-Seq. We validate the panel on a collection of representative human and animal samples, comparing it to qPCR and shotgun next-generation sequencing (NGS). AA-PCR-Seq provides a robust, straightforward method for screening large numbers of samples for virus detection and discovery.

genomics↗