Biology subjects

Huang, M.

Publications and source records attributed to Huang, M..

At least 181 records · Page 10Linked to original sources

bioRxiv2020

SARS-CoV-2 infection severity is linked to superior humoral immunity against the spike

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently causing a global pandemic. The antigen specificity and kinetics of the antibody response mounted against this novel virus are not understood in detail. Here, we report that subjects with a more severe SARS-CoV-2 infection exhibit a larger antibody response against the spike and nucleocapsid protein and epitope spreading to subdominant viral antigens, such as open reading frame 8 and non-structural proteins. Subjects with a greater antibody response mounted a larger memory B cell response against the spike, but not the nucleocapsid protein. Additionally, we revealed that antibodies against the spike are still capable of binding the D614G spike mutant and cross-react with the SARS-CoV-1 receptor binding domain. Together, this study reveals that subjects with a more severe SARS-CoV-2 infection exhibit a greater overall antibody response to the spike and nucleocapsid protein and a larger memory B cell response against the spike.

immunology↗

bioRxiv2020

Structural and biochemical mechanisms of NLRP1 inhibition by DPP9

The nucleotide-binding domain (NBD) and leucine-rich repeat (LRR)-containing receptors (NLRs) mediate innate immunity by forming inflammasomes. Activation of the NLR protein NLRP1 requires auto-cleavage within its FIIND domain1-7. In resting cells, the dipeptidyl peptidase DPP9 interacts with NLRP1-FIIND and together with a related enzyme DPP8, suppresses spontaneous NLRP1 activation8,9. The mechanisms of DPP8/9-mediated NLRP1 inhibition, however, remain elusive. Here we provide structural and biochemical evidence demonstrating that rat NLRP1 (rNLRP1) interacts with rDPP9 in a stepwise manner to form a 2:1 complex. An auto-inhibited rNLRP1 molecule first interacts with rDPP9 via its ZU5 domain. This 1:1 rNLRP1-rDPP9 complex then captures the UPA domain of a second rNLRP1 molecule via a UPA-interacting site on DPP9 and dimeric UPA-UPA interactions with the first rNLRP1. The 2:1 rNLRP1-rDPP9 complex prevents NLRP1 UPA-mediated higher order oligomerization and maintains NLRP1 in the auto-inhibited state. Structure-guided biochemical and functional assays show that both NLRP1-binding and its enzymatic activity are required for DPP9 to suppress NLRP1, supporting guard-type activation of the NLR. Together, our data reveal the mechanism of DPP9-mediated inhibition of NLRP1 and shed light on activation of the NLRP1 inflammasome.

immunology↗

bioRxiv2020

Dimension reduction and denoising of single-cell RNA sequencing data in the presence of observed confounding variables

Confounding variation, such as batch effects, are a pervasive issue in single-cell RNA sequencing experiments. While methods exist for aligning cells across batches, it is yet unclear how to correct for other types of confounding variation which may be observed at the subject level, such as age and sex, and at the cell level, such as library size and other measures of cell quality. On the specific problem of batch alignment, many questions still persist despite recent advances: Existing methods can effectively align batches in low-dimensional representations of cells, yet their effectiveness in aligning the original gene expression matrices is unclear. Nor is it clear how batch correction can be performed alongside data denoising, the former treating technical biases due to experimental stratification while the latter treating technical variation due inherently to the random sampling that occurs during library construction and sequencing. Here, we propose SAVERCAT, a method for dimension reduction and denoising of single-cell gene expression data that can flexibly adjust for arbitrary observed covariates. We benchmark SAVERCAT against existing single-cell batch correction methods and show that while it matches the best of the field in low-dimensional cell alignment, it significantly improves upon existing methods on the task of batch correction in the high-dimensional expression matrix. We also demonstrate the ability of SAVERCAT to effectively integrate batch correction and denoising through a data down-sampling experiment. Finally, we apply SAVERCAT to a single cell study of Alzheimers disease where batch is confounded with the contrast of interest, and demonstrate how adjusting for covariates other than batch allows for more interpretable analysis.

genomics↗

bioRxiv2020

SARS-CoV-2 ORF6 disrupts nucleocytoplasmic transport through interactions with Rae1 and Nup98

RNA viruses that replicate in the cytoplasm often disrupt nucleocytoplasmic transport to preferentially translate their own transcripts and prevent host antiviral responses. The Sarbecovirus accessory protein ORF6 has previously been shown to be the major inhibitor of interferon production in both SARS-CoV and SARS-CoV-2. SARS-CoV-2 ORF6 was recently shown to co-purify with the host mRNA export factors Rae1 and Nup98. Here, we demonstrate SARS-CoV-2 ORF6 strongly represses protein expression of co-transfected reporter constructs and imprisons host mRNA in the nucleus, which is associated with its ability to co-purify with Rae1 and Nup98. These protein-protein interactions map to the C-terminus of ORF6 and can be abolished by a single amino acid mutation in Met58. Overexpression of Rae1 restores reporter expression in the presence of SARS-CoV-2 ORF6. We further identify an ORF6 mutant containing a 9-amino acid deletion, ORF6 {Delta}22-30, in multiple SARS-CoV-2 clinical isolates that can still downregulate the expression of a co-transfected reporter and interact with Rae1 and Nup98. SARS-CoV ORF6 also interacts with Rae1 and Nup98. However, SARS-CoV-2 ORF6 more strongly co-purifies with Rae1 and Nup98 and results in significantly reduced expression of reporter proteins compared to SARS-CoV ORF6, a potential mechanism for the delayed symptom onset and pre-symptomatic transmission uniquely associated with the SARS-CoV-2 pandemic. ImportanceSARS-CoV-2, the causative agent of COVID-19, is an RNA virus with a large genome that encodes accessory proteins. While these accessory proteins are not required for growth in vitro, they can contribute to the pathogenicity of the virus. One of SARS-CoV-2s accessory proteins, ORF6, was recently shown to co-purify with two host proteins, Rae1 and Nup98, involved in mRNA nuclear export. We demonstrate SARS-CoV-2 ORF6 interaction with these proteins is associated with reduced expression of a reporter protein and accumulation of poly-A mRNA within the nucleus. SARS-CoV ORF6 also shows the same interactions with Rae1 and Nup98. However, SARS-CoV-2 ORF6 more strongly represses reporter expression and co-purifies with Rae1 and Nup98 compared to SARS-CoV ORF6. The ability of SARS-CoV-2 ORF6 to more strongly disrupt nucleocytoplasmic transport than SARS-CoV ORF6 may partially explain critical differences in clinical presentation between the two viruses.

microbiology↗

bioRxiv2020

Trantrace: a reliable, traceable, and collaborative solution to streamline the translation of emerging biomedical resources

BackgroundPrecision medicine is gaining popularity in routine health care, which heavily relies on the interpretation of emerging biomedical databases and professional guidelines. Translation of those biomedical materials, that is crucial to deliver research discovery to health interventions in non-native English-speaking countries, remains a large amount of work for biomedical practitioners. ResultsWe presented an application called Trantrace to facilitate the routine of large-scale long-running translation. Especially for the case that many people joined multiple translation projects, it has a rigorous task division and cooperation process: assignment, translation, review, release, and iteration. Trantrace empowers users to build own projects with different permissions, version control all the translation operation without specific skills, and further improve the translation efficiency through real-time task management tools. ConclusionsBy providing a working platform for collaborative translation and enabling long-time version correction, the Trantrace contributes towards the creation of a multilingual biomedical knowledge commons, which would be a valuable aid for personalized therapies. The source code is freely accessible at https://github.com/sgi-drylab/trantrace.

bioinformatics↗

bioRxiv2020

Detection of complex genetic architecture using two-locus population differentiation: modeling epistasis

Recent advances in genetics have increased our understanding of epistasis as important in the genetics of complex phenotypes. However, current analytical methods often cannot detect epistasis, given the multiple testing burden. To address this, we extended our previous method, Evolutionary Triangulation (ET), that uses differences among populations in both disease prevalence and allele frequencies to filter SNPs from association studies to generate novel interaction models. We show that two-locus ET identified several co-evolving gene pairs, where both genes associate with the same disease, and that the number of such pairs is significantly greater than expected by chance. Traits found by two-locus ET included those related to pigmentation and schizophrenia. We then applied two-locus ET to the analysis of preterm birth (PTB) genetics. Using ET to filter SNPs at loci identified by genome-wide association studies (GWAS), we showed that ET derived PTB two-locus models are novel and were not seen when only the index SNPs were used to generate epistatic models. One gene pair, ADCY5 and KCNAB1 5’, was identified as significantly interacting in a model of gestational age (p as low as 3 × 10−3). Notably, the same ET SNPs in these genes showed significant interactions in three of four cohorts analyzed. The robustness of this gene pair and others, demonstrated that the ET method can be used without prior biological hypotheses based on SNP function to select variants for epistasis testing that could not be identified otherwise. Two-locus ET clearly increased the ability to identify epistasis in complex traits.View Full Text

genetics↗

bioRxiv2020

In vivo antiviral host response to SARS-CoV-2 by viral load, sex, and age

Despite limited genomic diversity, SARS-CoV-2 has shown a wide range of clinical manifestations in different patient populations. The mechanisms behind these host differences are still unclear. Here, we examined host response gene expression across infection status, viral load, age, and sex among shotgun RNA-sequencing profiles of nasopharyngeal swabs from 430 individuals with PCR-confirmed SARS-CoV-2 and 54 negative controls. SARS-CoV-2 induced a strong antiviral response with upregulation of antiviral factors such as OAS1-3 and IFIT1-3, and Th1 chemokines CXCL9/10/11, as well as a reduction in transcription of ribosomal proteins. SARS-CoV-2 culture in human airway epithelial cultures replicated the in vivo antiviral host response. Patient-matched longitudinal specimens (mean elapsed time = 6.3 days) demonstrated reduction in interferon-induced transcription, recovery of transcription of ribosomal proteins, and initiation of wound healing and humoral immune responses. Expression of interferon-responsive genes, including ACE2, increased as a function of viral load, while transcripts for B cell-specific proteins and neutrophil chemokines were elevated in patients with lower viral load. Older individuals had reduced expression of Th1 chemokines CXCL9/10/11 and their cognate receptor, CXCR3, as well as CD8A and granzyme B, suggesting deficiencies in trafficking and/or function of cytotoxic T cells and natural killer (NK) cells. Relative to females, males had reduced B and NK cell-specific transcripts and an increase in inhibitors of NF-{kappa}B signaling, possibly inappropriately throttling antiviral responses. Collectively, our data demonstrate that host responses to SARS-CoV-2 are dependent on viral load and infection time course, with observed differences due to age and sex that may contribute to disease severity.

microbiology↗

bioRxiv2020

Multi-model evaluation of phenology prediction for wheat in Australia

Predicting wheat phenology is important for cultivar selection, for effective crop management and provides a baseline for evaluating the effects of global change. Evaluating how well crop phenology can be predicted is therefore of major interest. Twenty-eight wheat modeling groups participated in this evaluation. Our target population was wheat fields in the major wheat growing regions of Australia under current climatic conditions and with current local management practices. The environments used for calibration and for evaluation were both sampled from this same target population. The calibration and evaluation environments had neither sites nor years in common, so this is a rigorous evaluation of the ability of modeling groups to predict phenology for new sites and weather conditions. Mean absolute error (MAE) for the evaluation environments, averaged over predictions of three phenological stages and over modeling groups, was 9 days, with a range from 6 to 20 days. Predictions using the multi-modeling group mean and median had prediction errors nearly as small as the best modeling group. About two thirds of the modeling groups performed better than a simple but relevant benchmark, which predicts phenology by assuming a constant temperature sum for each development stage. The added complexity of crop models beyond just the effect of temperature was thus justified in most cases. There was substantial variability between modeling groups using the same model structure, which implies that model improvement could be achieved not only by improving model structure, but also by improving parameter values, and in particular by improving calibration techniques.

plant biology↗

bioRxiv2020

Gut microbiota impairs insulin clearance during obesity

Hyperinsulinemia can be a cause and consequence of obesity and insulin resistance. Increased insulin secretion and reduced insulin clearance can contribute to hyperinsulinemia. The triggers for changes in insulin clearance during obesity are ill-defined. We found that oral antibiotics mitigated impaired insulin clearance in mice fed a high fat diet (HFD) for 12 weeks or longer. Short-term HFD feeding and aging did not alter insulin clearance in mice. Germ-free mice colonized with microbes from HFD-fed mice had impaired insulin clearance, but not C-peptide clearance, and only after mice were colonized for 6 weeks and then HFD-fed. Five bacterial taxa predicted >90% of the variance in insulin clearance. Our data indicate that gut microbes are an independent and transmissible factor that regulates obesity-induced changes in insulin clearance. A small cluster of microbes may be a target for mitigating defects in insulin clearance and the progression of obesity and Type 2 Diabetes. We propose that a small community in the gut microbiota can impair insulin clearance and increase insulin load and the risk of complications from hyperinsulinemia.

physiology↗

bioRxiv2020

Expression and in vitro anticancer activity of Lp16-PSP, a member of the YjgF/YER057c/UK114protein family from the mushroom Lentinula edodes C91-3

Latcripin-16 (Lp16-PSP) is a gene that was extracted as a result of de novo characterization of the Lentinula edodes strain C91-3 transcriptome. The aim of the present study was to clone, express and investigate the selective in vitro anticancer potential of Lp16-PSP in human cell lines. Lp16-PSP was analyzed using bioinformatics tools, cloned in a prokaryotic expression vector pET32a (+) and transformed into E. coli Rosetta gami. It was expressed and solubilized under optimized conditions. The differential scanning fluorometry (DSF)-guided refolding method was used with modifications to identify the proper refolding conditions for the Lp16-PSP protein. In order to determine the selective anticancer potential of Lp16-PSP, a panel of human cancerous and non-cancerous cell lines was used. Lp16-PSP protein was identified as endoribonuclease L-PSP protein and a member of the highly conserved YjgF/YER057c/UK114 protein superfamily. Lp16-PSP was expressed under optimized conditions (37{degrees}C for 4 h following induction with 0.5 mM isopropyl {beta}-D-1-thiogalactopyranoside). Solubilization was achieved with mild solubilization buffer containing 2M urea using the freeze-thaw method. The DSF guided refolding method identified the proper refolding conditions (50 mM Tris-HCl, 100 mM NaCl, 1 mM EDTA, 400 mM Arginine, 0.2 mM GSH and 2 mM GSSG; pH 8.0) for Lp16-PSP, with a melting transition of ~58{degrees}C. A final yield of ~16 mg of purified Lp16-PSP from 1 L of culture was obtained following dialysis and concentration by PEG 20,000. A Cell Counting Kit-8 assay revealed the selective cytotoxic effect of Lp16-PSP. The HL-60 cell line was demonstrated to be most sensitive to Lp16-PSP, with an IC50 value of 74.4{+/-}1.07 g/ml. The results of the present study suggest that Lp16-PSP may serve as a potential anticancer agent; however, further investigation is required to characterize this anticancer effect and to elucidate the molecular mechanism underlying the action of Lp16-PSP.

cancer biology↗

bioRxiv2020

Large-scale Inference of Population Structure in Presence of Missingness using PCA

BackgroundPrincipal component analysis (PCA) is a commonly used tool in genetics to capture and visualize population structure. Due to technological advances in sequencing, such as the widely used non-invasive prenatal test, massive datasets of ultra-low coverage sequencing are being generated. These datasets are characterized by having a large amount of missing genotype information. We present EMU, a method for inferring population structure in the presence of rampant non-random missingness. ResultsWe show through simulations that several commonly used PCA methods can not handle missing data arisen from various sources, which leads to biased results as individuals are projected into the PC space based on their amount of missingness. In terms of accuracy, EMU outperforms an existing method that also accommodates missingness while being competitively fast. We further tested EMU on around 100K individuals of the Phase 1 dataset of the Chinese Millionome Project, that were shallowly sequenced to around 0.08x. From this data we are able to capture the population structure of the Han Chinese and to reproduce previous analysis in a matter of CPU hours instead of CPU years. ConclusionsEMUs capability to accurately infer population structure in the presence of missingness will be of increasing importance with the rising number of large-scale genetic datasets. EMU is written in Python and is freely available at https://github.com/Rosemeis/emu/.

genetics↗

bioRxiv2020

Population genetics of sugar kelp in the Northwest Atlantic region using genome-wide markers

An assessment of genetic diversity of marine populations is critical not only for the understanding and preservation of natural biodiversity but also for its economic potential. As commercial demand rises for marine resources, it is critical to generate baseline information for monitoring wild populations. Furthermore, anthropogenic stressors on the coastal environment, such as warming sea surface temperatures and overharvesting of wild populations, are leading to the destruction of keystone marine species such as kelps. In this study, we conducted a fine-scale genetic analysis using genome-wide high-density markers on Northwest Atlantic sugar kelp species, Saccharina latissima and putative species, Saccharina angustissima. The population structure for a total of 149 samples from the Gulf of Maine (GOM) and Southern New England (SNE) was investigated using AMOVA, Fst, admixture, and PCoA. Genome-wide association analyses were conducted for six morphological traits, and the extended Lewontin and Krakauer (FLK) test was used to detect selection signatures. Our results indicate that the GOM region is moderately more heterogeneous than SNE. While admixture was observed between regions, these results confirm that Cape Cod acts as a biogeographic barrier for sugar kelp gene flow. We detected one significant SNP (P-value=2.03x10-7) associated with stipe length, and 243 SNPs with higher-than-neutral differentiation. The findings of this study provide fundamental knowledge on sugar kelp population genetics for future monitoring, managing and potentially restoring wild populations, as well as assisting in selective breeding to improve desirable traits for cultivation and bioenergy production.

genetics↗

bioRxiv2020

Cancer SIGVAR: A semi-automated interpretation tool for germline variants of hereditary cancer-related genes

The American College of Medical Genetics and Genomics and the Association for Molecular Pathology published guidelines in 2015 for the clinical interpretation of Mendelian disorder sequence variants based on 28 criteria. ClinGen Sequence Variant Interpretation (SVI) Working Groups have developed many adaptations or refinements of these guidelines to improve the consistency of interpretation. We combined the most recent adaptations to expand the criteria from 28 to 48 and developed a tool called Cancer SIGVAR to help healthcare workers and genetic counselors interpret the clinical significance of cancer germline variants, which is critical for the clinical diagnosis and treatment of hereditary cancer. Our tool can accept VCF files as input and realize fully automated interpretation based on 21 criteria and semi-automated interpretation based on 48 criteria. We validated our tool on the ClinVar and CLINVITAE benchmark databases for the accuracy of fully automated interpretation, achieving an average consistency for pathogenic and benign assessment up to 93.40% and 82.54%, respectively. We compared Cancer SIGVAR with a similar tool, InterVar, and analyzed the main differences in criteria and implementation. In addition, to verify the performance of semi-automated interpretation based on 48 criteria, we selected 911 variants from two benchmark databases and reached an average classification consistency of 98.35%. Our findings highlight the need to optimize automated interpretation tools based on constantly updated guidelines.

genetics↗

bioRxiv2020

Quantify the requirements to achieve grain Zn biofortification of high-yield wheat on calcareous soils

The solution to address global human Zn deficiency is Zn biofortification of staple food crops, aimed at high grain Zn concentration as well as high yield. However, the desired high grain Zn concentration above 40 mg kg-1 is rarely observed for high-yield wheat on worldwide calcareous soils, due to inadequate Zn uptake or Zn distribution to grain. The present study aims to investigate how much Zn uptake or distribution is adequate to achieve the Zn.t of high-yield wheat on calcareous soils with low available Zn ([~] 0.5 mg kg-1). Of the 123 cultivars tested in a three-year field experiment, 19 high-yield cultivars were identified with similar yields around 7.0 t ha-1 and various grain Zn concentrations from 9.3 to 26.7 mg kg-1. The adequate Zn distribution to grain was defined from the view of Zn biofortification, as the situation where the Zn distribution to grain (Zn harvest index) increased to the observed maximum of [~] 91.0% and the Zn concentration of vegetative parts (straw Zn concentration) decreased to the observed minimum of [~] 1.5 mg kg-1 (Zn.m). Under the assumed condition of adequate Zn distribution to grain ([~] 91.0%), all the extra Zn above Zn.m was remobilized from straw to grain and the grain Zn concentration would be increased to its highest attainable level, which was 14.5 [~] 31.3 mg kg-1 for the 19 high-yield cultivars but still lower than 40 mg kg-1. Thus, even with the adequate Zn distribution to grain, the current Zn uptake is still not adequate and needs to be increased to 308 g ha-1 or higher to achieve Zn.t for high-yield wheat (7.0 t ha-1) on low-Zn calcareous soils. Besides, the established method here can also provide the priority measures and quantitative guidelines to achieve Zn biofortification in other wheat production regions.

plant biology↗

bioRxiv2020

Comparative secretome of Magnaporthe oryzae identified proteins involved in virulence and cell wall integrity

Plant fungal pathogens secrete numerous proteins into the apoplast at the plant-fungus contact sites to facilitate colonization. Only a few secreted proteins were functionally characterized in Magnaporthe oryzae, the fungal pathogen causing rice blast disease worldwide. ALG3 is an -1, 3-mannosyltransferase function in N-glycan synthesis for secreted N-glycosylated proteins, and the {Delta}alg3 mutants show strong defects in cell wall integrity and fungal virulence, indicating a potential effect on the secretion of multiple proteins. In this study, we compared the secretome of wild type and {Delta}alg3 mutants, and identified 51 proteins that require ALG3 for proper secretion. These are predicted to be involved in metabolic processes, interspecies interactions, cell wall organization, and response to chemicals. The tested secreted proteins localized at the apoplast region surrounding the fungal infection hyphae. Moreover, the N-glycosylation of candidate proteins was significantly changed in the {Delta}alg3 mutant, leading to the reduction of protein secretion and abnormal protein localization. Furthermore, we tested the function of two genes, one is a previously reported M. oryzae gene Invertase 1 (INV1) encoding a secreted invertase, and the other one is a gene encoding an Acid mammalian chinitase (AMCase). The fungal virulence was significantly reduced and the cell wall integrity was altered in the {Delta}inv1 and {Delta}amcase mutant strains. Elucidation of the comparative secretome of M. oryzae improves our understanding of the proteins that require ALG3 for secretion, and of their function in fungal virulence and cell wall integrity.

plant biology↗

bioRxiv2020

The type 2 diabetes gene product STARD10 is a phosphoinositide binding protein that controls insulin secretory granule biogenesis

ObjectiveRisk alleles for type 2 diabetes at the STARD10 locus are associated with lowered STARD10 expression in the {beta}-cell, impaired glucose-induced insulin secretion and decreased circulating proinsulin:insulin ratios. Although likely to serve as a mediator of intracellular lipid transfer, the identity of the transported lipids, and thus the pathways through which STARD10 regulates {beta}-cell function, are not understood. The aim of this study was to identify the lipids transported and affected by STARD10 in the {beta}-cell and its effect on proinsulin processing and insulin granule biogenesis and maturation. MethodsWe used isolated islets from mice deleted selectively in the {beta}-cell for Stard10 ({beta}StarD10KO) and performed electron microscopy, pulse-chase, RNA sequencing and lipidomic analyses. Proteomic analysis of STARD10 binding partners was executed in INS1 (832/13) cell line. X-ray crystallography followed by molecular docking and lipid overlay assay were performed on purified STARD10 protein. Results{beta}StarD10KO islets had a sharply altered dense core granule appearance, with a dramatic increase in the number of "rod-like" dense cores. Correspondingly, basal secretion of proinsulin was increased. Amongst the differentially expressed genes in {beta}StarD10KO islets, expression of the phosphoinositide binding proteins Pirt and Synaptotagmin 1 were decreased while lipidomic analysis demonstrated changes in phosphatidyl inositol levels. The inositol lipid kinase PIP4K2C was also identified as a STARD10 binding partner. STARD10 bound to inositides phosphorylated at the 3 position and solution of the crystal structure of STARD10 to 2.3 [A] resolution revealed a binding pocket capable of accommodating polyphosphoinositides. ConclusionOur data indicate that STARD10 binds to, and may transport, phosphatidylinositides, influencing membrane lipid composition, insulin granule biosynthesis and insulin processing.

cell biology↗

bioRxiv2020

Isolation and Characterization of 2019-nCoV-like Coronavirus from Malayan Pangolins

The outbreak of 2019-nCoV in the central Chinese city of Wuhan at the end of 2019 poses unprecedent public health challenges to both China and the rest world1. The new coronavirus shares high sequence identity to SARS-CoV and a newly identified bat coronavirus2. While bats may be the reservoir host for various coronaviruses, whether 2019-nCoV has other hosts is still ambiguous. In this study, one coronavirus isolated from Malayan pangolins showed 100%, 98.2%, 96.7% and 90.4% amino acid identity with 2019-nCoV in the E, M, N and S genes, respectively. In particular, the receptor-binding domain of the S protein of the Pangolin-CoV is virtually identical to that of 2019-nCoV, with one amino acid difference. Comparison of available genomes suggests 2019-nCoV might have originated from the recombination of a Pangolin-CoV-like virus with a Bat-CoV-RaTG13-like virus. Infected pangolins showed clinical signs and histopathological changes, and the circulating antibodies reacted with the S protein of 2019-nCoV. The isolation of a coronavirus that is highly related to 2019-nCoV in the pangolins suggests that these animals have the potential to act as the intermediate host of 2019-nCoV. The newly identified coronavirus in the most-trafficked mammal could represent a continuous threat to public health if wildlife trade is not effectively controlled.

microbiology↗

bioRxiv2020

Estimation of Full-Length TprK Diversity in Treponema pallidum subspecies pallidum

Immune evasion and disease progression of Treponema pallidum subspecies pallidum are associated with sequence diversity in the hypervariable, putative outer membrane protein TprK. Previous attempts to study variation within TprK have sequenced at depths insufficient to fully appreciate the hypervariable nature of the protein, failed to establish linkage between the proteins 7 variable regions, or were conducted on strains passed through rabbits. As a consequence, a complete profiling of tprK during infection in the human host is still lacking. Furthermore, prior studies examining how T. pallidum uses its repertoire of genomic donor sites to generate diversity within the V regions of the tprK also yielded a partial understanding of this process, due to the limited number of tprK alleles examined. In this study, we used short- and long-read deep sequencing to directly characterize full-length tprK alleles from T. pallidum collected from early lesions of patients attending two STD clinics in Italy. Our data, combined with recent data available on Chinese T. pallidum strains, show the near complete absence of overlap in TprK sequences among the 41 strains profiled to date. Moreover, our data allowed us to redefine the boundaries of tprK V regions, identify 55 donor sites, and estimate the total number of TprK variants that T. pallidum can potentially generate. Altogether, our results support how T. pallidum TprK antigenic variation system is an unsurmountable obstacle for the human immune system to naturally achieve infection eradication, and reiterate the importance of this mechanism for pathogen persistence in the host. ImportanceSyphilis continues to be a significant public health issue in both low- and high-income nations, including the United States, where the number of infectious syphilis cases has increased dramatically over the past five years. T. pallidum, the causative agent of syphilis, encodes an outer membrane protein TprK that undergoes segmental gene conversion to constantly create new sequences. We performed deep TprK profiling to understand full-length TprK diversity in T. pallidum-positive clinical specimens and compared these to all samples for which TprK deep sequencing is available. We found almost no overlap in TprK sequences between different patients. We further estimate that the total baseline junctional diversity of full-length TprK rivals that of current estimates of the human adaptive immune system. These data underscore the immunoevasive ability of TprK that allows T. pallidum to establish lifelong infection.

microbiology↗