Structure and dynamics of the proton-selective histidine and the gating tryptophan in an inward rectifying hybrid influenza B and A virus M2 proton channel.

The M2 proteins of influenza A and B viruses form acid-activated proton channels that are essential for the virus lifecycle. Proton selectivity is achieved by a transmembrane (TM) histidine whereas gating is achieved by a tryptophan residue. Although this functional apparatus is conserved between AM2 and BM2 channels, AM2 conducts protons exclusively inward whereas BM2 conducts protons in either direction depending on the pH gradient. Previous studies showed that in AM2, mutations of D44 abolished inward rectification of AM2, suggesting that the tryptophan gate is destabilized. To elucidate how charged residues C-terminal to the tryptophan regulates channel gating, here we investigate the structure and dynamics of H19 and W23 in a BM2 mutant, GDR-BM2, in which three BM2 residues are mutated to the corresponding AM2 residues, S16G, G26D and H27R. Whole-cell electrophysiological data show that GDR-BM2 conducts protons with inward rectification, identical to wild-type (WT) AM2 but different from WT-BM2. Solid-state NMR 15N and 13C spectra of H19 indicate that the mutant BM2 channel contains higher populations of cationic histidine and neutral τ tautomers compared to WT-BM2 at acidic pH. Moreover, 19F NMR spectra of 5-19F-labeled W23 resolve three peaks at acidic pH, suggesting three tryptophan sidechain conformations. Comparison of these spectra with the tryptophan spectra of other M2 peptides suggests that these indole sidechain conformations arise from interactions with the C-terminal charged residues and with the N-terminal cationic histidine. Taken together, these solid-state NMR data show that inward rectification in M2 proton channels is accomplished by tryptophan interactions with charged residues on both its C-terminal and N-terminal sides. Gating of these M2 proton channels is thus accomplished by a multi-residue complex with finely tuned electrostatic and aromatic interactions.

Single-base tiled screen unveils design principles of PspCas13b for potent and off-target-free RNA silencing.

The development of precise RNA-editing tools is essential for the advancement of RNA therapeutics. CRISPR (clustered regularly interspaced short palindromic repeats) PspCas13b is a programmable RNA nuclease predicted to offer superior specificity because of its 30-nucleotide spacer sequence. However, its design principles and its on-target, off-target and collateral activities remain poorly characterized. Here, we present single-base tiled screening and computational analyses that identify key design principles for potent and highly selective RNA recognition and cleavage in human cells. We show that the de novo design of spacers containing guanosine bases at precise positions can greatly enhance the catalytic activity of inefficient CRISPR RNAs (crRNAs). These validated design principles (integrated into an online tool, https://cas13target.azurewebsites.net/ ) can predict highly effective crRNAs with ~90% accuracy. Furthermore, the comprehensive spacer-target mutagenesis revealed that PspCas13b can tolerate only up to four mismatches and requires ~26-nucleotide base pairing with the target to activate its nuclease domains, highlighting its superior specificity compared to other RNA or DNA interference tools. On the basis of this targeting resolution, we predict an extremely low probability of PspCas13b having off-target effects on other cellular transcripts. Proteomic analysis validated this prediction and showed that, unlike other Cas13 orthologs, PspCas13b exhibits potent on-target activity and lacks collateral effects.

Therapeutic drug monitoring of osimertinib in EGFR mutant non-small cell lung cancer by dried blood spot and plasma collection: A pilot study.

AIMS: Therapeutic drug monitoring (TDM) has led to significant improvements in individualized medical care, although its implementation in oncology has been limited to date. Tyrosine kinase inhibitors (TKIs) are a group of therapies for which TDM has been suggested. Osimertinib is one such therapy used in the treatment of epidermal growth factor receptor (EGFR) mutation-driven lung cancer. Herein, we describe a prospective pilot study involving 21 patients on osimertinib primarily as a preliminary evaluation of drug levels in a real-world setting. METHODS: Concentrations of the drug and its primary metabolites were measured with a validated liquid chromatography-mass spectrometry (LC-MS) assay across serial timepoints. As part of this study, inter-individual variability by dose and ethnicity as well as intra-individual variability across timepoints are explored. Furthermore, we attempted to validate dried blood spot (DBS)-based quantitation as an accurate alternative to plasma quantitation. RESULTS: Successful quantitation of osimertinib and primary metabolites was achieved for our subjects. Compound plasma levels were highly correlated to DBS levels. There was no significant difference in concentrations with ethnicity or dosing or intra-individual variability across timepoints. CONCLUSIONS: As such, we demonstrate that TDM for osimertinib is practical for future trials. We also validated the use of DBS as an alternative to conventional quantitation for exploration of TDM for osimertinib in larger trials and for other targeted therapies.

Seasonal antigenic prediction of influenza A H3N2 using machine learning.

Antigenic characterization of circulating influenza A virus (IAV) isolates is routinely assessed by using the hemagglutination inhibition (HI) assays for surveillance purposes. It is also used to determine the need for annual influenza vaccine updates as well as for pandemic preparedness. Performing antigenic characterization of IAV on a global scale is confronted with high costs, animal availability, and other practical challenges. Here we present a machine learning model that accurately predicts (normalized) outputs of HI assays involving circulating human IAV H3N2 viruses, using their hemagglutinin subunit 1 (HA1) sequences and associated metadata. Each season, the model learns an updated nonlinear mapping of genetic to antigenic changes using data from past seasons only. The model accurately distinguishes antigenic variants from non-variants and adaptively characterizes seasonal dynamics of HA1 sites having the strongest influence on antigenic change. Antigenic predictions produced by the model can aid influenza surveillance, public health management, and vaccine strain selection activities.

Novel combinatorial autophagy inhibition therapy for triple negative breast cancers.

BACKGROUND: Triple negative breast cancer (TNBC) has the worst prognosis among breast cancer subtypes. It is characterized by lack of estrogen, progesterone and human epidermal growth factor 2 receptors, and thus, have limited therapeutic options. Autophagy has been found to be correlated with poor prognosis and aggressive behaviour in TNBC. This study aimed to target autophagy in TNBC via a novel approach to inhibit TNBC progression. METHODS: Immunoblotting and confocal microscopy were carried out to examine the effect of tumor microenvironmental stressors on autophagy. Cellular proliferation and migration assays were used to test the effect of different autophagy inhibitors and standard chemotherapy alone or in combination. In vivo xenograft mouse model was utilized to assess the effect of autophagy inhibitors alone or in combination with Paclitaxel. High resolution mass spectrometry based proteomic analysis was performed to explore the mechanisms behind chemoresistance in TNBC. Lastly, immunohistochemistry was done to assess the correlation between autophagy related proteins and clinical characteristics in TNBC tissue specimens. RESULTS: Metabolic stressors were found to induce autophagy in TNBC cell lines. Autophagy initiation inhibitors, SAR405 and MRT68921, showed marked synergy in their anti-proliferative activity in both chemosensitive and chemoresistant TNBC cell models. Paradoxically, positive expression of autophagosome marker LC3 was shown to be associated with better overall survival of TNBC patients. CONCLUSION: In this study, a novel combination between different autophagy inhibitors was identified which inhibited tumor cell proliferation in both chemosensitive and chemoresistant TNBC cells and could result in development of a novel treatment modality against TNBC.

Novel serum protein biomarker panel for early diagnosis of pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers. Late presentation of disease at the time of diagnosis is one of the major reasons for dismal prognostic outcomes for PDAC patients. Currently, there is a lack of clinical biomarkers, which can be used to diagnose PDAC patients at an early resectable stage. This study performed proteomic mass spectrometry to identify novel blood-based biomarkers for early diagnosis of PDAC. Serum specimens from 88 PDAC patients and 88 healthy controls (60 discovery cohort and 28 validation cohort) were analyzed using data independent acquisition high resolution mass spectrometry to identify candidate biomarker proteins. A total of 249 proteins were identified and quantified by the mass spectrometric analysis. Six proteins were markedly (>1.5 fold) and significantly (p < .05; q < 0.1) increased in PDAC patients compared to healthy controls in discovery cohort. Notably, four of these six proteins were significantly upregulated in an independent validation cohort. The top three upregulated proteins (i.e., Polymeric Immunoglobulin Receptor [PIGR], von Willebrand Factor [vWF], and Fibrinogen) were validated using enzyme linked immunosorbent assay, which led to selection of PIGR and vWF as a diagnostic biomarker panel for PDAC. The panel showed high ability to diagnose early stage (stage I and II) PDAC patients (area under the curve [AUC]: 0.8926), which was further improved after the addition of clinically used prognostic biomarker (Ca 19-9) to the panel (AUC: 0.9798). In conclusion, a novel serum protein biomarker panel for early diagnosis of PDAC was identified.

Cross-Reactivity Assessment of Vaccine-Derived SARS-CoV-2 T Cell Responses against BA.2.86 and JN.1.

The SARS-CoV-2 Omicron sub-variants BA.2.86 and JN.1 contain multiple mutations in the spike protein that were not present in previous variants of concern and Omicron sub-variants. Preliminary research suggests that these variants reduce the neutralizing capability of antibodies induced by vaccines, which is particularly significant for JN.1. This raises concern as many widely deployed COVID-19 vaccines are based on the spike protein of the ancestral Wuhan strain of SARS-CoV-2. While T cell responses have been shown to be robust against previous SARS-CoV-2 variants, less is known about the impact of mutations in BA.2.86 and JN.1 on T cell responses. We evaluate the effect of mutations specific to BA.2.86 and JN.1 on experimentally determined T cell epitopes derived from the spike protein of the ancestral Wuhan strain and the spike protein of the XBB.1.5 strain that has been recommended as a booster vaccine. Our data suggest that BA.2.86 and JN.1 affect numerous T cell epitopes in spike compared to previous variants; however, the widespread loss of T cell recognition against these variants is unlikely.

Proteome profiling of enriched membrane-associated proteins unraveled a novel sophorose and cello-oligosaccharide transporter in Trichoderma reesei.

BACKGROUND: Trichoderma reesei is an organism extensively used in the bioethanol industry, owing to its capability to produce enzymes capable of breaking down holocellulose into simple sugars. The uptake of carbohydrates generated from cellulose breakdown is crucial to induce the signaling cascade that triggers cellulase production. However, the sugar transporters involved in this process in T. reesei remain poorly identified and characterized. RESULTS: To address this gap, this study used temporal membrane proteomics analysis to identify five known and nine putative sugar transporters that may be involved in cellulose degradation by T. reesei. Docking analysis pointed out potential ligands for the putative sugar transporter Tr44175. Further functional validation of this transporter was carried out in Saccharomyces cerevisiae. The results showed that Tr44175 transports a variety of sugar molecules, including cellobiose, cellotriose, cellotetraose, and sophorose. CONCLUSION: This study has unveiled a transporter Tr44175 capable of transporting cellobiose, cellotriose, cellotetraose, and sophorose. Our study represents the first inventory of T. reesei sugar transportome once exposed to cellulose, offering promising potential targets for strain engineering in the context of bioethanol production.

A Validated Assay to Quantify Osimertinib and Its Metabolites, AZ5104 and AZ7550, from Microsampled Dried Blood Spots and Plasma.

BACKGROUND: Osimertinib is an oral small-molecule tyrosine kinase receptor inhibitor used to treat non-small cell lung cancer (NSCLC) with a sensitizing epidermal growth factor receptor mutation. Patients may experience drug toxicity and require dose deescalation. The study aimed to quantitate osimertinib and its 2 active metabolites, AZ5104 and AZ7550, in microsampled dried blood spots (DBS) collected from patients with NSCLC using a hemaPEN device and compare them with plasma drug levels. METHODS: A 6-min ultrahigh-performance liquid chromatography-tandem mass spectrometry method was developed and validated using plasma and DBS. The accuracy, selectivity, matrix effect, recovery, and stability were assessed using bioanalytical validation criteria. The hematocrit effect was investigated in DBS. Drug levels were measured in 15 patients with NSCLC, and the Bland-Altman method was used to compare measurements between plasma and DBS. RESULTS: The validated assay determined accurate and precise quantities, respectively, for osimertinib in both plasma (93.2%-99.3%; 0.2%-2.3%) and DBS (96.7%-99.6%; 0.5%-10.3%) over a concentration of 1-729 ng/mL. The osimertinib metabolites, AZ5104 and AZ7550, were similarly validated in accordance with bioanalytical guidelines. For 30%-60% patient hematocrit, no hematocrit bias was observed with DBS for all analytes. The Bland-Altman method showed high concordance between plasma and DBS analyte levels. Stability experiments revealed that osimertinib and its metabolites were poorly stable in plasma at room temperature, whereas all analytes were stable in DBS for 10 days at room temperature. CONCLUSIONS: The measurement of osimertinib, AZ5104, and AZ7550 from hemaPEN microsampled DBS is a convenient and reliable approach for therapeutic drug monitoring that produces measurements consistent with plasma drug levels.

Inhibition of autophagy initiation: A novel strategy for oral squamous cell carcinomas.

BACKGROUND: Oral squamous cell carcinoma (OSCC) is one of the most common forms of oral cancer and is known to have poor prognostic outcomes. Autophagy is known to be associated with aggressive tumor biology of OSCC. Hence, this study aimed to develop a novel therapeutic strategy against OSCC by targeting the autophagic pathway. METHODS: Immunoblotting, and confocal microscopy were used to examine the effect of tumor microenvironmental stressors on the autophagy activity. Cellular proliferation and migration assays were performed to assess the anti-cancer activity of standard chemotherapy and autophagy initiation inhibitors, either alone or in combination. High resolution mass-spectrometry based proteomic analysis was utilized to understand the mechanisms behind chemoresistance in OSCC models. Finally, immunohistochemistry was performed to determine associations between autophagy markers and clinicopathological characteristics. RESULTS: Tumor microenvironmental stressors were shown to induce autophagy activity in OSCC cell lines. Novel combinations of chemotherapy and autophagy inhibitors as well as different classes of autophagy inhibitors were identified. Combination of MRT68921 and SAR405 demonstrated marked synergy in their anti-proliferative activity and also showed synergy with chemotherapy in chemoresistant OSCC cell models. Autophagy was identified as one of the key pathways involved in mediating chemoresistance in OSCC. Furthermore, TGM2 was identified as a key upstream regulator of chemoresistance in OSCC models. Finally, positive staining for autophagosome marker LC3 was shown to be associated with low histological grade OSCC. CONCLUSION: In conclusion, this study identified a combination of novel autophagy inhibitors which can potently inhibit proliferation of both chemosensitive as well as chemoresistant OSCC cells and could be developed as a novel therapy against advanced OSCC tumors.

HCV E1 influences the fitness landscape of E2 and may enhance escape from E2-specific antibodies.

The Hepatitis C virus (HCV) envelope glycoprotein E1 forms a non-covalent heterodimer with E2, the main target of neutralizing antibodies. How E1-E2 interactions influence viral fitness and contribute to resistance to E2-specific antibodies remain largely unknown. We investigate this problem using a combination of fitness landscape and evolutionary modeling. Our analysis indicates that E1 and E2 proteins collectively mediate viral fitness and suggests that fitness-compensating E1 mutations may accelerate escape from E2-targeting antibodies. Our analysis also identifies a set of E2-specific human monoclonal antibodies that are predicted to be especially resilient to escape via genetic variation in both E1 and E2, providing directions for robust HCV vaccine development.

Direct-acting antiviral resistance of Hepatitis C virus is promoted by epistasis.

Direct-acting antiviral agents (DAAs) provide efficacious therapeutic treatments for chronic Hepatitis C virus (HCV) infection. However, emergence of drug resistance mutations (DRMs) can greatly affect treatment outcomes and impede virological cure. While multiple DRMs have been observed for all currently used DAAs, the evolutionary determinants of such mutations are not currently well understood. Here, by considering DAAs targeting the nonstructural 3 (NS3) protein of HCV, we present results suggesting that epistasis plays an important role in the evolution of DRMs. Employing a sequence-based fitness landscape model whose predictions correlate highly with experimental data, we identify specific DRMs that are associated with strong epistatic interactions, and these are found to be enriched in multiple NS3-specific DAAs. Evolutionary modelling further supports that the identified DRMs involve compensatory mutational interactions that facilitate relatively easy escape from drug-induced selection pressures. Our results indicate that accounting for epistasis is important for designing future HCV NS3-targeting DAAs.

Within-host genetic diversity of SARS-CoV-2 lineages in unvaccinated and vaccinated individuals.

Viral and host factors can shape SARS-CoV-2 evolution. However, little is known about lineage-specific and vaccination-specific mutations that occur within individuals. Here, we analysed deep sequencing data from 2,820 SARS-CoV-2 respiratory samples with different viral lineages to describe the patterns of within-host diversity under different conditions, including vaccine-breakthrough infections. In unvaccinated individuals, variant of Concern (VOC) Alpha, Delta, and Omicron respiratory samples were found to have higher within-host diversity and were under neutral to purifying selection at the full genome level compared to non-VOC SARS-CoV-2. Breakthrough infections in 2-dose or 3-dose Comirnaty and CoronaVac vaccinated individuals did not increase levels of non-synonymous mutations and did not change the direction of selection pressure. Vaccine-induced antibody or T cell responses did not appear to have significant impact on within-host SARS-CoV-2 sequence diversification. Our findings suggest that vaccination does not increase exploration of SARS-CoV-2 protein sequence space and may not facilitate emergence of viral variants.

Proteome Analysis of Whole Blood Collected by Volumetric Absorptive Microsampling.

Proteomic biomarker discovery and analysis from human biofluids using liquid chromatography-mass spectrometry (LC-MS) is an area of intense biomedical research. There is a growing interest to analyze microsampled patient blood specimens as this is potentially more patient-friendly enabling at-home and bedside self-collection of small blood volumes. However, there are limited studies applying LC-MS proteomic analysis of whole blood as it is dominated by red blood cell proteins such as hemoglobin which suppresses the detection of other less abundant proteins. Volumetric absorptive microsampling (VAMS) devices overcome this issue in part by providing a trapping matrix which allows depletion of abundant blood cell proteins through washing, prior to proteolysis and LC-MS. This approach allows the analysis of proteins from erythrocytes, leukocytes, and plasma and leads to deeper proteomic coverage compared to conventional plasma proteomics, increasing the prospects to discover novel biomarker proteins.

Quantification of short-chain fatty acids in human stool samples by LC-MS/MS following derivatization with aniline analogues.

The gut microbiome produces a range of short chain fatty acids (SCFA) crucially linked with diet and nutrition, metabolism, gastrointestinal health and homeostasis. SCFA are primarily measured using gas or liquid chromatography-mass spectrometry (LC/MS) after undergoing chemical derivatization. Here we assess the merits of a derivatization protocol using aniline and two aniline analogues (3-phenoxyaniline and 4-(benzyloxy)aniline) for the targeted LC-MS/MS quantification of nine SCFA (acetic, propionic, butyric, valeric, caproic acid, isobutyric, isovaleric, 2-methylbutyric, and 2-ethylbutyric acid). Evaluation of product ion spectra and optimization of MS detection conditions, provided superior detection sensitivity for 3-phenoxyaniline and 4-(benzyloxy)aniline compared to aniline. We developed a facile SCFA derivatization method using 3-phenoxyaniline under mild reaction conditions which allows for the simultaneous quantification of these SCFA in human stool samples in under eleven minutes using multiple reaction monitoring LC-MS/MS. The method was successfully validated and demonstrates intra- and inter-day accuracy (88.5-103% and 86.0-109%) and precision (CV of 0.55-7.00% and 0.33-9.55%) with recoveries (80.1-87.2% for LLOQ, 88.5-93.0% for ULOQ) and carry-over of (2.68-17.9%). Selectivity, stability and matrix effects were also assessed and satisfied validation criteria. Method applicability was demonstrated by analysing SCFA profiles in DNA-stabilized human stool samples from newly diagnosed colorectal cancer patients prior to surgery. The development of this improved method and its compatibility to measure SCFAs from DNA-stabilized stool will facilitate studies investigating the gut microbiome in health and disease.

The Cytoplasmic Domain of the SARS-CoV-2 Envelope Protein Assembles into a ß-Sheet Bundle in Lipid Bilayers.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) envelope (E) protein forms a pentameric ion channel in the lipid membrane of the endoplasmic reticulum Golgi intermediate compartment (ERGIC) of the infected cell. The cytoplasmic domain of E interacts with host proteins to cause virus pathogenicity and may also mediate virus assembly and budding. To understand the structural basis of these functions, here we investigate the conformation and dynamics of an E protein construct (residues 8-65) that encompasses the transmembrane domain and the majority of the cytoplasmic domain using solid-state NMR. 13C and 15N chemical shifts indicate that the cytoplasmic domain adopts a ß-sheet-rich conformation that contains three ß-strands separated by turns. The five subunits associate into an umbrella-shaped bundle that is attached to the transmembrane helices by a disordered loop. Water-edited NMR spectra indicate that the third ß-strand at the C terminus of the protein is well hydrated, indicating that it is at the surface of the ß-bundle. The structure of the cytoplasmic domain cannot be uniquely determined from the inter-residue correlations obtained here due to ambiguities in distinguishing intermolecular and intramolecular contacts for a compact pentameric assembly of this small domain. Instead, we present four structural topologies that are consistent with the measured inter-residue contacts. These data indicate that the cytoplasmic domain of the SARS-CoV-2 E protein has a strong propensity to adopt ß-sheet conformations when the protein is present at high concentrations in lipid bilayers. The equilibrium between the ß-strand conformation and the previously reported α-helical conformation may underlie the multiple functions of E in the host cell and in the virion.

Vaccinia-Virus-Based Vaccines Are Expected to Elicit Highly Cross-Reactive Immunity to the 2022 Monkeypox Virus.

Beginning in May 2022, a novel cluster of monkeypox virus infections was detected in humans. This virus has spread rapidly to non-endemic countries, sparking global concern. Specific vaccines based on the vaccinia virus (VACV) have demonstrated high efficacy against monkeypox viruses in the past and are considered an important outbreak control measure. Viruses observed in the current outbreak carry distinct genetic variations that have the potential to affect vaccine-induced immune recognition. Here, by investigating genetic variation with respect to orthologous immunogenic vaccinia-virus proteins, we report data that anticipates immune responses induced by VACV-based vaccines, including the currently available MVA-BN and ACAM2000 vaccines, to remain highly cross-reactive against the newly observed monkeypox viruses.

Inferring Epistasis from Genetic Time-series Data.

Epistasis refers to fitness or functional effects of mutations that depend on the sequence background in which these mutations arise. Epistasis is prevalent in nature, including populations of viruses, bacteria, and cancers, and can contribute to the evolution of drug resistance and immune escape. However, it is difficult to directly estimate epistatic effects from sampled observations of a population. At present, there are very few methods that can disentangle the effects of selection (including epistasis), mutation, recombination, genetic drift, and genetic linkage in evolving populations. Here we develop a method to infer epistasis, along with the fitness effects of individual mutations, from observed evolutionary histories. Simulations show that we can accurately infer pairwise epistatic interactions provided that there is sufficient genetic diversity in the data. Our method also allows us to identify which fitness parameters can be reliably inferred from a particular data set and which ones are unidentifiable. Our approach therefore allows for the inference of more complex models of selection from time-series genetic data, while also quantifying uncertainty in the inferred parameters.

Within-host diversity of SARS-CoV-2 lineages and effect of vaccination.

Viral and host factors can shape SARS-CoV-2 within-host viral diversity and virus evolution. However, little is known about lineage-specific and vaccination-specific mutations that occur within individuals. Here we analysed deep sequencing data from 2,146 SARS-CoV-2 samples with different viral lineages to describe the patterns of within-host diversity in different conditions, including vaccine-breakthrough infections. Variant of Concern (VOC) Alpha, Delta, and Omicron samples were found to have higher within-host nucleotide diversity while being under weaker purifying selection at full genome level compared to non-VOC SARS-CoV-2 viruses. Breakthrough Delta and Omicron infections in Comirnaty and CoronaVac vaccinated individuals appeared to have higher within-host purifying selection at the full-genome and/or Spike gene levels. Vaccine-induced antibody or T cell responses did not appear to have significant impact on within-host SARS-CoV-2 evolution. Our findings suggest that vaccination does not increase SARS-CoV-2 protein sequence space and may not facilitate emergence of more viral variants.

Identifying genetic determinants of inflammatory pain in mice using a large-scale gene-targeted screen.

ABSTRACT: Identifying the genetic determinants of pain is a scientific imperative given the magnitude of the global health burden that pain causes. Here, we report a genetic screen for nociception, performed under the auspices of the International Mouse Phenotyping Consortium. A biased set of 110 single-gene knockout mouse strains was screened for 1 or more nociception and hypersensitivity assays, including chemical nociception (formalin) and mechanical and thermal nociception (von Frey filaments and Hargreaves tests, respectively), with or without an inflammatory agent (complete Freund's adjuvant). We identified 13 single-gene knockout strains with altered nocifensive behavior in 1 or more assays. All these novel mouse models are openly available to the scientific community to study gene function. Two of the 13 genes (Gria1 and Htr3a) have been previously reported with nociception-related phenotypes in genetically engineered mouse strains and represent useful benchmarking standards. One of the 13 genes (Cnrip1) is known from human studies to play a role in pain modulation and the knockout mouse reported herein can be used to explore this function further. The remaining 10 genes (Abhd13, Alg6, BC048562, Cgnl1, Cp, Mmp16, Oxa1l, Tecpr2, Trim14, and Trim2) reveal novel pathways involved in nociception and may provide new knowledge to better understand genetic mechanisms of inflammatory pain and to serve as models for therapeutic target validation and drug development.