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Martin, J.

Publications and source records attributed to Martin, J..

At least 109 records · Page 6Linked to original sources

One pathway, two cyclic pentapeptides: heterologous expression of BE-18257 A-C and pentaminomycins A-E from Streptomyces cacaoi CA-170360

1.The strain Streptomyces cacaoi CA-170360 produces the cyclic pentapeptides pentaminomycins A-E and BE-18257 A-C, two families of cyclopeptides synthesized by two nonribosomal peptide synthetases encoded in tandem within the same biosynthetic gene cluster. In this work, we have cloned and confirmed the heterologous expression of this biosynthetic gene cluster, demonstrating that each of the nonribosomal peptide synthetases present in the cluster is involved in the biosynthesis of each group of cyclopeptides. In addition, we discuss the involvement of a stand-alone enzyme belonging to the Penicillin Binding Protein family in the release and macrocyclization of the peptides.

molecular biology↗

The proteasome-related Connectase is a fast and specific protein ligase

Genetic methods allow the recombinant production of any protein of interest, but yield the full-length construct in one step and are limited to native amino acids. For the "on demand" generation of chimeric, immobilized, fluorophore-conjugated or segmentally labeled proteins, these proteins must be modified using chemical1,2, (split) intein2,3, split domain4 or enzymatic methods5. While each of these options comes with its own advantages and drawbacks, ligase enzymes are often used where small ligation motifs and good chemoselectivity are required. However, applications with the reference enzyme Sortase A are impeded by poor catalytic efficiencies, low substrate specificities and side reactions6,7. Here, we present the discovery of Connectase, a monomeric proteasome homolog that ligates substrates via a highly conserved KDPGA motif originally identified in methyltransferase A (MtrA), a key enzyme in archaeal methanogenesis. Connectase displays nanomolar affinity and thus great specificity for its substrates, allowing efficient protein-protein ligations even in complex solutions and at low substrate concentrations. Compared to an optimized Sortase variant, Connectase catalyzes such ligations at substantially higher rates, with higher yields but without detectable side reactions and thus presents a valuable new tool for protein conjugations.

biochemistry↗

IFN signaling and neutrophil degranulation transcriptional signatures are induced during SARS-CoV-2 infection

The novel virus SARS-CoV-2 has infected more than 14 million people worldwide resulting in the Coronavirus disease 2019 (COVID-19). Limited information on the underlying immune mechanisms that drive disease or protection during COVID-19 severely hamper development of therapeutics and vaccines. Thus, the establishment of relevant animal models that mimic the pathobiology of the disease is urgent. Rhesus macaques infected with SARS-CoV-2 exhibit disease pathobiology similar to human COVID-19, thus serving as a relevant animal model. In the current study, we have characterized the transcriptional signatures induced in the lungs of juvenile and old rhesus macaques following SARS-CoV-2 infection. We show that genes associated with Interferon (IFN) signaling, neutrophil degranulation and innate immune pathways are significantly induced in macaque infected lungs, while pathways associated with collagen formation are downregulated. In COVID-19, increasing age is a significant risk factor for poor prognosis and increased mortality. We demonstrate that Type I IFN and Notch signaling pathways are significantly upregulated in lungs of juvenile infected macaques when compared with old infected macaques. These results are corroborated with increased peripheral neutrophil counts and neutrophil lymphocyte ratio in older individuals with COVID-19 disease. In contrast, pathways involving VEGF are downregulated in lungs of old infected macaques. Using samples from humans with SARS-CoV-2 infection and COVID-19, we validate a subset of our findings. Finally, neutrophil degranulation, innate immune system and IFN gamma signaling pathways are upregulated in both tuberculosis and COVID-19, two pulmonary diseases where neutrophils are associated with increased severity. Together, our transcriptomic studies have delineated disease pathways to improve our understanding of the immunopathogenesis of COVID-19 to facilitate the design of new therapeutics for COVID-19.

immunology↗

A normative account of choice history effects in mice and humans

Choice history effects describe how future choices depend on the history of past choices. Choice history effects are typically framed as a bias rather than an adaptive phenomenon because the phenomenon generally degrades reward rates in experimental tasks. How-ever, in natural habitats, choices made in the past constrain choices that can be made in the future. For foraging animals, the probability of obtaining a reward in a given patch depends on the degree to which the animals have exploited the patch in the past. One problem with many experimental tasks that show choice history effects is that such tasks artificially decouple choice history from its consequences in regard to reward availability over time. To circumvent this, we used a variable interval (VI) reward schedule that reinstates a more natural contingency between past choices and future reward availability. By manipulating first- and second-order statistics of the environment, we dissociated choice history, reward history, and reaction times. We found that choice history effects reflect the growth rate of the reward probability of the unchosen option, reward history effects reflect environmental volatility, and reaction time reflects overall reward rate. By testing in mice and humans, we show that the same choice history effects can be generalized across species and that these effects are similar to those observed in optimal agents. Furthermore, we develop a new reinforcement learning model that explicitly incorporates choice history over multiple timescales into the decision process, and we examine its predictive adequacy in accounting for the associated behavioral data. We show that this new variant, known as the double trace model, has a higher predictive adequacy of choice data, in addition to better reward harvesting efficiency in simulated environments. Finally, we show that the choice history effects emerge in optimal models of foraging in habitats with diminishing returns, thus linking this phenomenon to a wider class of optimality models in behavioral ecology. These results suggests that choice history effects may be adaptive for natural contingencies between consumption and reward availability. This concept lends credence to a normative account of choice history effects that extends beyond its description as a bias.

neuroscience↗

CITEseq analysis of non-small-cell lung cancer lesions reveals an axis of immune cell activation associated with tumor antigen load and TP53 mutations

Immunotherapy is becoming a mainstay in the treatment of NSCLC. While tumor mutational burden (TMB) has been shown to correlate with response to immunotherapy, little is known about the relation of the baseline immune response with the tumor genotype. Here, we profiled 35 early stage NSCLC lesions using multiscale single cell sequencing. Unsupervised clustering identified in a subset of patients a key cellular module consisting of PDCD1+ CXCL13+ activated T cells, IgG+ plasma cells, and SPP1+ macrophages, referred to as the lung cancer activation module (LCAMhi). Transcriptional data from two NSCLC cohorts confirmed a subset of patients with LCAMhi enrichment, which was independent of overall immune cell content. The LCAMhi module strongly correlated with TMB, expression of cancer testis antigens, and with TP53 mutations in smokers and non-smokers. These data establish LCAM as a key mode of immune cell activation associated with high tumor antigen load and driver mutations.

immunology↗

Allosteric inhibition of adenylyl cyclase type 5 by G-protein: a molecular dynamics study

Adenylyl cyclases (ACs) have a crucial role in many signal transduction pathways, in particular in the intricate control of cyclic AMP (cAMP) generation from adenosine triphosphate (ATP). Using homology models developed from existing structural data and docking experiments, we have carried out all-atom, microsecond-scale molecular dynamics simulations on the AC5 isoform of adenylyl cyclase bound to the inhibitory G-protein subunit Gi in the presence and in the absence of ATP. The results show that Gi have significant effects on the structure and flexibility of adenylyl cyclase, as observed earlier for the binding of ATP and Gs. New data on Gi bound to the C1 domain of AC5 help to explain how Gi inhibits enzyme activity and to get insight on its regulation. Simulations also suggest a crucial role of ATP in the regulation of stimulation and inhibition of AC5. Author summaryThe neurons that compose the human brain are able to respond to multiple inputs from other neurons. The chemical "integration" of these inputs then decides whether a given neuron passes on a signal or not. External chemical messages act on neurons via proteins in their membranes that trigger cascades of reactions within the cell. One key molecule in these signaling cascades is cyclic adenosine monophosphate (cAMP) that is chemically synthesized from adenosine triphosphate (ATP) by the enzyme adenylyl cyclase (AC). We are investigating the mechanisms that control how much cAMP is produced as a function of the signals received by the neuron. In particular, we have studied the inhibition effect of a key protein, termed Gi, on AC, and we compare it with the stimulator effect of another key protein termed Gs. Using microsecond molecular simulations, we have been able to show how binding Gi to AC changes its structure and its dynamics so that its enzymatic activity is quenched and that ATP seems to have a crucial role in the regulation of stimulation and inhibition of AC5.

molecular biology↗

Distinguishing within from between individual effects: How to use the within-individual centering method for quadratic pattern

O_LIAny average pattern observed at the population level may confound two different types of processes: some processes that occur among individuals and others that occur within individuals. Separating within- from among-individual processes is critical for our understanding of ecological and evolutionary dynamics. C_LIO_LIThe within-individual centering method allows distinguishing within- from among-individual processes and this method has been largely used in ecology to investigate both linear and quadratic patterns. Here we show that two alternative equations could be used for the investigation of quadratic within-individual patterns. We explain under which hypotheses each is valid. Reviewing the literature, we found that mainly one of these two equations has been used by the studies investigating quadratic patterns. Yet this equation could be inappropriate in many cases. C_LIO_LIWe show that these two alternative equations make different assumptions about the shape of the within-individual pattern. The choice of using one equation instead of the other should depend upon the biological process investigated. One equation assumes that all individuals show the same quadratic pattern over the whole range of the explanatory variable whereas the other assumes that the quadratic patterns depend on the average explanatory variable of each individual. We give examples of biological processes corresponding to each equation. C_LIO_LIUsing simulations, we showed that a mismatch between the assumptions made by the equation used to analyze the data and the biological process investigated led to flawed inference affecting both output of model selection and accuracy of estimates. We stress that the equation used should be chosen carefully to ensure that the assumption made about the shape of the within-individual pattern matches the biological process investigated. We hope that this manuscript will encourage the use of the within-individual centering method, promoting its correct application for non-linear relationships. C_LI

ecology↗

Examining sex-differentiated genetic effects across neuropsychiatric and behavioral traits

BackgroundThe origin of sex differences in prevalence and presentation of neuropsychiatric and behavioral traits is largely unknown. Given established genetic contributions and correlations across these traits, we tested for a sex-differentiated genetic architecture within and between traits. MethodsUsing genome-wide association study (GWAS) summary statistics for 20 neuropsychiatric and behavioral traits, we tested for differences in SNP-based heritability (h2) and genetic correlation (rg<1) between sexes. For each trait, we computed z-scores from sex-stratified GWAS regression coefficients and identified genes with sex-differentiated effects. We calculated Pearson correlation coefficients between z-scores for each trait pair, to assess whether specific pairs share variants with sex-differentiated effects. Finally, we tested for sex differences in between-trait genetic correlations. ResultsWith current sample sizes (and power), we found no significant, consistent sex differences in SNP-based h2. Between-sex, within-trait genetic correlations were consistently high, although significantly less than 1 for educational attainment and risk-taking behavior. We identified genome-wide significant genes with sex-differentiated effects for eight traits. Several trait pairs shared sex-differentiated effects. The top 0.1% of genes with sex-differentiated effects across traits overlapped with neuron- and synapse-related gene sets. Most between-trait genetic correlation estimates were similar across sex, with several exceptions (e.g. educational attainment & risk-taking behavior). ConclusionsSex differences in the common autosomal genetic architecture of neuropsychiatric and behavioral phenotypes are small and polygenic, requiring large sample sizes. Genes with sex-differentiated effects are enriched for neuron-related gene sets. This work motivates further investigation of genetic, as well as environmental, influences on sex differences.

genetics↗

Rapid and sensitive direct detection and identification of poliovirus from stool and environmental surveillance samples using nanopore sequencing

Global poliovirus surveillance involves virus isolation from stool and environmental samples, intratypic differential (ITD) by PCR and sequencing of the VP1 region to distinguish vaccine (Sabin), vaccine-derived and wild-type polioviruses and ensure an appropriate response. This cell-culture algorithm takes 2-3 weeks on average between sample receipt and sequencing. Direct detection of viral RNA using PCR allows faster detection but has traditionally faced challenges related to poor sensitivity and difficulties in sequencing common samples containing poliovirus and enterovirus mixtures. We present a nested PCR and nanopore sequencing protocol that allows rapid (<3 days) and sensitive direct detection and sequencing of polioviruses in stool and environmental samples. We developed barcoded primers and a real-time analysis platform that generate accurate VP1 consensus sequences from multiplexed samples. The sensitivity and specificity compared with cell-culture were 90.9% (95% Confidence Interval: 75.7-98.1%) and 99.2% (95.5-100.0%) for wild-type 1 poliovirus, 92.5% (79.6-98.4%) and 98.7% (95.4-99.8%) for vaccine and vaccine-derived serotype 2 poliovirus, and 88.3% (81.2-93.5%) and 93.2% (88.6-96.3%) for Sabin 1 and 3 poliovirus alone or in mixtures when tested on 155 stool samples in Pakistan. Variant analysis of sequencing reads also allowed identification of polioviruses and enteroviruses in artificial mixtures and was able to distinguish complex mixtures of polioviruses in environmental samples. The median identity of consensus nanopore sequences with Sanger or Illumina sequences from the same samples was >99.9%. This novel method shows promise as a faster and safer alternative to cell-culture for the detection and real-time sequencing of polioviruses in stool and environmental samples.

microbiology↗

Rescoring ensembles of protein-protein docking poses using consensus approaches

Scoring is a challenging step in protein-protein docking, where typically thousands of solutions are generated. Successful scoring is more often based on physicochemical evaluation of the generated interfaces and/or statistical potentials that reproduce known interface properties. Another route is offered by consensus-based rescoring, where the set of solutions is used to build statistics in order to identify recurrent solutions. We explore several ways to perform consensus-based rescoring on the ZDOCK decoy set for Benchmark 4. We show that the information of the interface size is critical for successful rescoring. We combine consensus-based rescoring with the ZDOCK native scoring function and show that this improves the initial results.

bioinformatics↗

Investigating regions of shared genetic variation in attention deficit/hyperactivity disorder and major depressive disorder: A GWAS meta-analysis

Attention deficit/hyperactivity disorder (ADHD) demonstrates a high level of comorbidity with major depressive disorder (MDD). One possible contributor to this is that the two disorders show high genetic correlation. However, the specific regions of the genome that may be responsible for this overlap are unclear. To identify variants associated with both ADHD and MDD, we performed a meta-analysis of GWAS of ADHD and MDD. All genome wide significant (p=5x10-8) SNPs in the meta-analysis that were also strongly associated (p=5x10-4) independently with each disorder were followed up. These putatively pleiotropic SNPs were tested for additional associations across a broad range of phenotypes. Fourteen linkage disequilibrium-independent SNPs were identified that were associated with each disorder separately (p=5x10-4) and in the cross-disorder meta-analysis (p=5x10-8). Nine of these SNPs had not been reported previously in either individual GWAS and can be considered as novel signals. Evidence supported nine of the fourteen SNPs acting as eQTL and two of the SNPs as brain eQTL. Index SNPs and their genomic regions demonstrated associations with other mental health phenotypes. Through conducting meta-analysis on ADHD and MDD only, our results build upon the previously observed genetic correlation between ADHD and MDD and reveal novel regions of the genome that may be implicated in this overlap.

genetics↗

Single cell transcriptional characterization of human megakaryocyte lineage commitment and maturation

In the current understanding of adult bone marrow hematopoiesis, megakaryocytes (MKs) originate from cells immuno-phenotypically indistinguishable from hematopoietic stem cells (HSCs), bypassing intermediate progenitors. Here, we use single cell RNA sequencing to characterize HSCs and MKs from human bone marrow, to investigate MK lineage commitment and maturation. We identify two MK primed HSC clusters exhibiting unique differentiation kinetics, at least one of which is used in steady state and stress thrombopoiesis. By analyzing transcriptional signatures we show that human bone marrow MKs originate from MK primed HSC subpopulations, supporting the notion that these display exclusive priming for MK differentiation. We show that transcriptional programs change with increasing MK ploidy, where genes upregulated in high ploidy states may have functional relevance in platelet production. Finally, we highlight the presence of a specific transcriptional signature in MKs from individuals with myocardial infarction, supporting the aberration of MK differentiation in this thrombotic state.

cell biology↗

Improving characterization of understudied human microbiomes using targeted phylogenetics

Whole genome bacterial sequences are required to better understand microbial functions, niches-pecific bacterial metabolism, and disease states. Although genomic sequences are available for many of the human-associated bacteria from commonly tested body habitats (e.g. stool), as few as 13% of bacterial-derived reads from other sites such as the skin map to known bacterial genomes. To facilitate a better characterization of metagenomic shotgun reads from under-represented body sites, we collected over 10,000 bacterial isolates originating from 14 human body habitats, identified novel taxonomic groups based on full length 16S rRNA sequences, clustered the sequences to ensure that no individual taxonomic group was over-selected for sequencing, prioritized bacteria from under-represented body sites (such as skin, respiratory and urinary tract), and sequenced and assembled genomes for 665 new bacterial strains. Here we show that addition of these genomes improved read mapping rates of HMP metagenomic samples by nearly 30% for the previously under-represented phylum Fusobacteria, and 27.5% of the novel genomes generated here had high representation in at least one of the tested HMP samples, compared to 12.5% of the sequences in the public databases, indicating an enrichment of useful novel genomic sequences resulting from the prioritization procedure. As our understanding of the human microbiome continues to improve and to enter the realm of therapy developments, targeted approaches such as this to improve genomic databases will increase in importance from both an academic and clinical perspective. ImportanceThe human microbiome plays a critically important role in health and disease, but current understanding of the mechanisms underlying the interactions between the varying microbiome and the different host environments is lacking. Having access to a database of fully sequenced bacterial genomes provides invaluable insights into microbial functions, but currently sequenced genomes for the human microbiome have largely come from a limited number of body sites (primarily stool), while other sites such as the skin, respiratory tract and urinary tracts are under-represented, resulting in as little as 13% of bacterial-derived reads mapping to known bacterial genomes. Here, we sequenced and assembled 665 new bacterial genomes, prioritized from a larger database to select under-represented body sites and bacterial taxa in the existing databases. As a result, we substantially improve mapping rates for samples from the Human Microbiome Project and provide an important contribution to human bacterial genomic databases for future studies.

microbiology↗

Genetic Association Study of Childhood Aggression across raters, instruments and age

Childhood aggressive behavior (AGG) has a substantial heritability of around 50%. Here we present a genome-wide association meta-analysis (GWAMA) of childhood AGG, in which all phenotype measures across childhood ages from multiple assessors were included. We analyzed phenotype assessments for a total of 328 935 observations from 87 485 children aged between 1.5 and 18 years, while accounting for sample overlap. We also meta-analyzed within subsets of the data - i.e. within rater, instrument and age. SNP-heritability for the overall meta-analysis (AGGoverall) was 3.31% (SE=0.0038). We found no genome-wide significant SNPs for AGGoverall. The gene-based analysis returned three significant genes: ST3GAL3 (P=1.6E-06), PCDH7 (P=2.0E-06) and IPO13 (P=2.5E-06). All three genes have previously been associated with educational traits. Polygenic scores based on our GWAMA significantly predicted aggression in a holdout sample of children (variance explained = 0.44%) and in retrospectively assessed childhood aggression (variance explained = 0.20%). Genetic correlations (rg) among rater-specific assessment of AGG ranged from rg =0.46 between self- and teacher-assessment to rg =0.81 between mother- and teacher-assessment. We obtained moderate to strong rgs with selected phenotypes from multiple domains, but hardly with any of the classical biomarkers thought to be associated with AGG. Significant genetic correlations were observed with most psychiatric and psychological traits (range |rg| : 0.19 - 1.00), except for obsessive-compulsive disorder. Aggression had a negative genetic correlation (rg =~ -0.5) with cognitive traits and age at first birth. Aggression was strongly genetically correlated with smoking phenotypes (range |rg| : 0.46 - 0.60). The genetic correlations between aggression and psychiatric disorders were weaker for teacher-reported AGG than for mother- and self-reported AGG. The current GWAMA of childhood aggression provides a powerful tool to interrogate the rater-specific genetic etiology of AGG.

genomics↗

Enhanced nutrient uptake is sufficient to drive emergent cross-feeding between bacteria

Interactive microbial communities are ubiquitous, influencing biogeochemical cycles and host health. One widespread interaction is nutrient exchange, or cross-feeding, wherein metabolites are transferred between microbes. Some cross-fed metabolites, such as vitamins, amino acids, and ammonium (NH4+), are communally valuable and impose a cost on the producer. The mechanisms that enforce cross-feeding of communally valuable metabolites are not fully understood. Previously we engineered mutualistic cross-feeding between N2-fixing Rhodopseudomonas palustris and fermentative Escherichia coli. Engineered R. palustris excreted essential nitrogen as NH4+ to E. coli while E. coli excreted essential carbon as fermentation products to R. palustris. Here, we enriched for nascent cross-feeding in cocultures with wild-type R. palustris, not known to excrete NH4+. Emergent NH4+ cross-feeding was driven by adaptation of E. coli alone. A missense mutation in E. coli NtrC, a regulator of nitrogen scavenging, resulted in constitutive activation of an NH4+ transporter. This activity likely allowed E. coli to subsist on the small amount of leaked NH4+ and better reciprocate through elevated excretion of organic acids from a larger E. coli population. Our results indicate that enhanced nutrient uptake by recipients, rather than increased excretion by producers, is an underappreciated yet possibly prevalent mechanism by which cross-feeding can emerge.

microbiology↗

Seasonal Effects of Environmental Change on Yellow-Bellied Marmot Population Dynamics

Natural populations are exposed to seasonal variation in environmental factors that simultaneously affect several demographic rates (survival, development, reproduction). The resulting covariation in these rates determines population dynamics, but accounting for its numerous biotic and abiotic drivers is a significant challenge. Here, we use a factor-analytic approach to capture partially unobserved drivers of seasonal population dynamics. We use 40 years of individual-based demography from yellow-bellied marmots (Marmota flaviventer) to fit and project population models that account for seasonal demographic covariation using a latent variable. We show that this latent variable, by producing positive covariation among winter demographic rates, depicts a measure of environmental quality. Simultaneous, negative responses of winter survival and reproductive-status change to declining environmental quality result in a higher risk of population quasi-extinction, regardless of summer demography where recruitment takes place. We demonstrate how complex environmental processes can be summarized to understand population persistence in seasonal environments.

ecology↗

Detection of Enterovirus D68 in wastewater samples from the United Kingdom during outbreaks reported globally between 2015 and 2018

Detection of enterovirus D68 (EV-D68) in wastewater samples from the UK between December 2014 and December 2018 showed a marked seasonal distribution with a high proportion of samples containing EV-D68 during periods when identification of this virus in clinical samples was most common. This includes a recent upsurge of EV-D68 detection in respiratory samples from the United Kingdom between August and December 2018 associated with cases of acute flaccid myelitis, following similar reports in the USA. Phylogenetic analysis of EV-D68 sewage strains demonstrated that strains belonging to distinct genetic clades followed the same temporal distribution as that observed for EV-D68 clinical strains in the UK and that they showed very close genetic relationship with EV-D68 strains circulating elsewhere in the world during the same periods. The results demonstrated a clear association between detecting EV-D68 in wastewater and finding it in clinical samples which was somehow unexpected given that EV-D68 is rarely detected in stool samples. We conclude that the use of environmental surveillance is a valuable tool to detect and monitor outbreaks due to EV-68 infection.

microbiology↗

Structural diversity of oligomeric β-propellers with different numbers of identical blades

{beta}-Propellers arise through the amplification of a supersecondary structure element called a blade. This process produces toroids of between four and twelve repeats, which are almost always arranged sequentially in a single polypeptide chain. We found that new propellers evolve continuously by amplification from single blades. We therefore investigated whether such nascent propellers can fold as homo-oligomers before they have been fully amplified within a single chain. One-to six-bladed building blocks derived from two seven-bladed WD40 propellers yielded stable homo-oligomers with six to nine blades, depending on the size of the building block. High-resolution structures for tetramers of two blades, trimers of three blades, and dimers of four and five blades, respectively, show structurally diverse propellers and include a novel fold, highlighting the inherent flexibility of the WD40 blade. Our data support the hypothesis that subdomain-sized fragments can provide structural versatility in the evolution of new proteins.

biochemistry↗