Biology subjects

Swain, A.

Publications and source records attributed to Swain, A..

33 records · Page 2Linked to original sources

bioRxiv2021

Myeloid cell interferon responses correlate with clearance of SARS-CoV-2

The emergence of mutant SARS-CoV-2 strains associated with an increased risk of COVID-19-related death necessitates better understanding of the early viral dynamics, host responses and immunopathology. While studies have reported immune profiling using single cell RNA sequencing in terminal human COVID-19 patients, performing longitudinal immune cell dynamics in humans is challenging. Macaques are a suitable model of SARS-CoV-2 infection. We performed longitudinal single-cell RNA sequencing of bronchoalveolar lavage (BAL) cell suspensions from adult rhesus macaques infected with SARS-CoV-2 (n=6) to delineate the early dynamics of immune cells changes. The bronchoalveolar compartment exhibited dynamic changes in transcriptional landscape 3 days post-SARS-CoV-2-infection (3dpi) (peak viremia), relative to 14-17dpi (recovery phase) and pre-infection (baseline). We observed the accumulation of distinct populations of both macrophages and T-lymphocytes expressing strong interferon-driven inflammatory gene signature at 3dpi. Type I IFN response was highly induced in the plasmacytoid dendritic cells. The presence of a distinct HLADR+CD68+CD163+SIGLEC1+ macrophage population exhibiting higher angiotensin converting enzyme 2 (ACE2) expression was also observed. These macrophages were significantly recruited to the lungs of macaques at 3dpi and harbored SARS-CoV-2, while expressing a strong interferon-driven innate anti-viral gene signature. The accumulation of these responses correlated with decline in viremia and recovery. The recruitment of a myeloid cell-mediated Type I IFN response is associated with the rapid clearance of SARS-CoV-2 infection in macaques.

immunology↗

bioRxiv2021

Lung epithelial signaling mediates early vaccine-induced CD4+ T cell activation and Mtb control

Tuberculosis (TB) is one of the leading causes of death due to a single infectious agent. The development of a TB vaccine that induces durable and effective immunity to Mycobacterium tuberculosis (Mtb) infection is urgently needed. Early and superior Mtb control can be induced in M. bovis Bacillus Calmette-Guerin (BCG) vaccinated hosts when the innate immune response is targeted to generate effective vaccine-induced immunity. In the present study, we show that innate activation of DCs is critical for mucosal localization of clonally activated vaccine-induced CD4+ T cells in the lung, and superior early Mtb control. In addition, our study reveals that Th1/Th17 cytokine axis play an important role in superior vaccine induced immunity. Our studies also show that activation of nuclear factor kappa-light-chain-enhancer of activated B cells (NF{kappa}{beta}) pathway in lung epithelial cells is critical for the mucosal localization of activated vaccine-induced CD4+ T cells for rapid Mtb control. Thus, our study provides novel insights into the immune mechanisms that can overcome TB vaccine bottlenecks and provide early rapid Mtb control. ImportanceTuberculosis is a leading cause of death due to single infectious agent accounting 1.4 million deaths each year. The only licensed vaccine BCG is not effective due to variable efficacy. In our study, we determined the early immune events necessary for achieving complete protection in BCG vaccinated host. Our study reveals that innate activation of DCs can mediate superior and early Mtb control in BCG vaccinated host through lung epithelial cell signaling and localization of clonal activated, Mtb antigen specific, cytokine producing CD4+ T cells within the lung parenchyma and airways. Thus, our study provides novel insights into the immune mechanisms that can overcome TB vaccine bottlenecks and provide early rapid Mtb control.

immunology↗

bioRxiv2021

Interactions, information and emergence: Exploring task allocation in ant colonies using network analysis

In animal societies, individuals may take on different roles to fulfil their own needs and the needs of their groups. Ant colonies display high levels of organisational complexity, with ants fulfilling different roles at different timescales (what is known as task allocation). Factors affecting task allocation can be at the individual level (e.g., physiology), or at the group level (e.g., the network of interactions). We focus on group level processes by exploring the relationship between interaction networks, task allocation and task switching using a previously published dataset (Mersch et al., 2013) tracking the behaviour of six Camponotus fellah colonies over 41 days. In our new analyses, our goal was to better explain the noisy process of task switching beyond simple age polyethism. First, we investigated the architecture of interaction networks using node (individual) level network measures and their relation to the individuals task - foraging, cleaning or nursing - and whether or not the ant switched tasks. We then explored how noisy information propagation was among ants, as a function of the colony composition (how many ants carried out which tasks), through the information-theoretic metric of Effective Information. Our results show that interaction history was tied to task allocation: ants who switched to a task are more likely to have interacted with other ants carrying out that task. The degree to which interactions related to task allocation, as well as the noise in those interactions, depended on which groups of ants were interacting. Overall, we showed that colony cohesion was stable even as ant-level network measures varied more for ants when they switched functional groups; thus, ant colonies maintained a high level of information flow as determined by network analysis, and ant functional groups played different roles in maintaining colony cohesion through varied information flows. HighlightsO_LIWe analysed the interaction networks of six Camponotus fellah colonies C_LIO_LIWe tested how centrality and information flow were tied to task switching C_LIO_LINode-level network metrics and the information theoretic measure of Effective Information explained differences among functional groups C_LIO_LIInteractions were correlated with task switching, but the strength of the correlation differed across functional groups C_LI

animal behavior and cognition↗

bioRxiv2021

Animal soundscapes reveal key markers of Amazon forest degradation from fire and logging

Safeguarding tropical forest biodiversity requires solutions for monitoring ecosystem composition over time. In the Amazon, logging and fire reduce forest carbon stocks and alter tree species diversity, but the long-term consequences for wildlife remain unclear, especially for lesser-known taxa. Here, we combined data from multi-day acoustic surveys, airborne lidar, and satellite timeseries covering logged and burned forests (n=39) in the southern Brazilian Amazon to identify acoustic markers of degradation. Our findings contradict theoretical expectations from the Acoustic Niche Hypothesis that animal communities in more degraded habitats occupy fewer acoustic niches. Instead, we found that habitat structure (e.g., aboveground biomass) was not a consistent proxy for biodiversity based on divergent patterns of acoustic space occupancy (ASO) in logged and burned forests. Full 24-hr soundscapes highlighted a stark and sustained reorganization in community structure after multiple fires; animal communication networks were quieter, more homogenous, and less acoustically integrated in forests burned multiple times than in logged or once-burned forests. These findings demonstrate strong biodiversity co-benefits from protecting Amazon forests from recurrent fire activity. By contrast, soundscape changes after logging were subtle and more consistent with community recovery than reassembly. In both logged and burned forests, insects were the dominant acoustic markers of degradation, particularly during midday and nighttime hours that are not typically sampled by traditional field surveys of biodiversity. The acoustic fingerprints of degradation history were conserved across replicate recording locations at each site, indicating that soundscapes offer a robust, taxonomically inclusive solution for tracking changes in community composition over time. Significance StatementFire and logging reduce the carbon stored in Amazon forests, but little is known about how human degradation alters animal communities. We recorded thousands of hours of ecosystem sounds to investigate animal community assembly and the associations between biodiversity and biomass following Amazon forest degradation over time. 24-hr patterns of acoustic activity differed between logged and burned forests, and we observed large and sustained breakpoints in community structure after multiple burns. Soundscape differences among degraded forests were clearest during insect-dominated hours rarely sampled in field studies of biodiversity. These findings demonstrate that acoustic monitoring holds promise for routine biodiversity accounting, even by non-experts, to capture a holistic measure of animal communities in degraded tropical forests and benchmark change over time.

ecology↗

bioRxiv2021

Spatial microbial community dynamics using a continuous species interaction model

The assembly and maintenance of microbial diversity in natural communities, despite the abundance of toxin-based antagonistic interactions, presents major challenges for biological understanding. A common framework for investigating such antagonistic interactions involve cyclic dominance games with pairwise interactions. The incorporation of higher-order interactions in such models permits increased levels of microbial diversity, especially in communities where antibiotic producing, sensitive, and resistant strains co-exist. However, most such models involve a small number of discrete species, assume a notion of pure cyclic dominance, and focus on low mutation rate regimes, none of which well represents the highly interlinked, quickly evolving, and continuous nature of microbial phenotypic space. Here, we present an alternative vision of spatial dynamics for microbial communities based on antagonistic interactions--one in which a large number of species interact in continuous phenotypic space, are capable of rapid mutation, and engage in both direct and higher-order interactions mediated by production of and resistance to antibiotics. Focusing on toxin production, vulnerability, and inhibition among species, we observe highly divergent patterns of diversity and spatial community dynamics. We find that species interaction constraints (rather than mobility) best predict spatiotemporal disturbance regimes, whereas community formation time, mobility, and mutation size best explain patterns of diversity. We also report an intriguing relationship among community formation time, spatial disturbance regimes, and diversity dynamics. This relationship, which suggests that both higher-order interactions and rapid evolution are critical for the origin and maintenance of microbial diversity, has broad-ranging links to the maintenance of diversity in other systems. Significance StatementPersistently diverse microbial communities are one of biologys great puzzles. Using a novel continuous trait space modeling framework that accommodates high mutation rates, elevated species richness, and direct and higher-order antagonistic species interactions, we find that two parameters characterizing mutation size and mobility best explain patterns of microbial diversity. Moreover, community formation time (the duration of the transient phase in community assembly) provides an unexpectedly clear guide to the diversity profiles of the resulting communities. These discoveries showcase how complex, antagonistic interactions mediated by the production of, inhibition of, and vulnerability to toxins (antibiotics) can shape microbial communities, allowing for extraordinarily high levels of diversity and temporal persistence.

systems biology↗

bioRxiv2020

PKA drives paracrine crisis and WNT4-dependent testis tumor in Carney complex

Large Cell Calcifying Sertoli Cell Tumors (LCCSCTs) are among the most frequent lesions occurring in Carney complex (CNC) male patients. Although they constitute a key diagnostic criterion for this rare multiple neoplasia syndrome resulting from inactivating mutations of the tumor suppressor PRKAR1A leading to unrepressed PKA activity, the LCCSCT pathogenesis and origin remain elusive. Mouse models targeting Prkar1a inactivation in all somatic populations or separately in each cell type were generated to decipher the molecular and paracrine networks involved in the CNC testis lesion induction. We demonstrate that Prkar1a mutation is required in both stromal and Sertoli cells for the occurrence of LCCSCT. Integrative analyses comparing transcriptomic, immunohistological data and phenotype of mutant mouse combinations led to understand the human LCCSCT pathogenesis and demonstrated unprecedented PKA-induced paracrine molecular circuits in which the aberrant WNT4 signal production is a limiting step in shaping intratubular lesions and tumor expansion both in mouse model and human CNC testes.

pathology↗

bioRxiv2020

Were Neoarchean atmospheric methane hazes and early Paleoproterozoic glaciations driven by the rise of oxygen in surface environments?

Geochemical evidence suggests methane was the predominant greenhouse gas in the Archean and early Proterozoic eons. Consequently, fluctuations in methane concentration in Earths atmosphere (i.e., methane hazes) would have contributed to climate change and influenced the flux of UV radiation reaching surface environments. If correct, understanding what factors (e.g., O2 and/or resource concentration) drove the biological methane cycle might shed light on the repetition of biological, atmospheric and climatic events preserved in the sedimentary rock record from ~2.8 to 2.0 BYA. To explore these interdependencies, we developed a novel dynamical model of microbial ecological interactions to investigate the conditions under which methane is preferentially released to the atmosphere. We found that the interplay between resource and O2 availability results in complex cyclic methane dynamics unrelated to the functional groups or efficiencies of microbial communities, to initial conditions, or to other model constraints. Based on these results, we propose that the cyclicity of methane haze events and glacial episodes in the Neoarchean and early Paleoproterozoic may have been linked to the progressive increase in oceanic and atmospheric O2 through the interval.

systems biology↗

bioRxiv2020

Effects of substrate availability on growth and metabolism in soil microbes: Insights from theoretical modeling of studies of the Warburg effect and substrate-induced respiration

Carbon Use Efficiency (CUE) is a popular concept for measuring the efficiency of biomass production in different biological systems and, is frequently employed to understand effects of microbial processes on soil carbon dynamics. CUE in soil microbes is often measured through respiration-based studies, especially through the addition of a labile carbon substrate such as glucose. Therefore, exploring the response of microbial respiration to availability of labile substrates is crucial to understand microbial CUE in soils. In this work, we build upon a cellular model of the Warburg effect, where cells simultaneously utilize inefficient aerobic glycolysis/fermentation and efficient oxidative phosphorylation pathways for energy synthesis even at high oxygen availability, to predict microbial community response to various levels of substrate availability. We test our predictions systematically using a series of substrate-induced respiration (SIR) experiments to demonstrate prevalence of the Warburg effect in soil microbial communities. We further discuss the relevance of the underlying metabolic processes behind the Warburg effect in interpreting soil microbial CUE.

microbiology↗

bioRxiv2020

Resilience and evolvability of protein-protein interaction networks

Protein-protein interaction (PPI) networks represent complex intra-cellular protein interactions, and the presence or absence of such interactions can lead to biological changes in an organism. Recent network-based approaches have shown that a phenotypes PPI networks resilience to environmental perturbations is related to its placement in the tree of life; though we still do not know how or why certain intra-cellular factors can bring about this resilience. Here, we explore the influence of gene expression and network properties on PPI networks resilience. We use publicly-available data of PPIs for E. coli, S. cerevisiae, and H. sapiens, where we compute changes in network resilience as new nodes (proteins) are added to the networks under three node addition mechanisms--random, degree-based, and gene-expression-based attachments. By calculating the resilience of the resulting networks, we estimate the effectiveness of these node addition mechanisms. We demonstrate that adding nodes with gene-expression-based preferential attachment (as opposed to random or degree-based) preserves and can increase the original resilience of PPI network in all three species, regardless of gene expression distribution or network structure. These findings introduce a general notion of prospective resilience, which highlights the key role of network structures in understanding the evolvability of phenotypic traits.

systems biology↗

bioRxiv2020

Deciphering trophic interactions in a mid-Cambrian assemblage

The Cambrian Period (541-485 Mya) represents a major stage in the development of metazoan-dominated assemblages with complex community structure and species interactions. Exceptionally preserved fossil sites have allowed specimen-based identification of putative trophic interactions to which network analyses have been applied. However, network analyses of the fossil record suffer from incomplete and indirect data, time averaging that obscures species coexistence, and biases in preservation. Here, we present a novel high-resolution fossil dataset from the Raymond Quarry (RQ) member of the mid-Cambrian Burgess Shale (7549 specimens, 61 taxa, ~510 Mya) affording new perspectives on these challenging issues. Further, we formulate a new measure of preservation bias that aids identification of those assemblage subsets to which network analyses can be reliably applied. For sections with sufficiently low bias, abundance correlation network analyses predicted longitudinally consistent trophic and competitive interactions. Our correlation network analyses predicted previously postulated trophic interactions with 83.5% accuracy and demonstrated a shift from specialist interaction-dominated assemblages to ones dominated by generalist and competitive interactions. This approach provides a robust, taphonomically corrected framework to explore and predict in detail the existence and ecological character of putative interactions in fossil datasets, offering new windows on ancient food-webs. Significance StatementUnderstanding interactions in paleo-ecosystems has been a difficult task due to biases in collection and preservation of taxa, as well as low time resolution of data. In this work, we use network science tools and a fine scale dataset from the Cambrian period to explore: (i) preservation bias due to ecological/physical characteristics of taxa; (ii) evidence that the magnitude and sign of pairwise abundance correlations between two fossil taxa yields information concerning the ecological character about the interaction. All results in our work derive from using complex system approaches to analyze abundance data, without assuming any prior knowledge about species interactions - thereby providing a novel general framework to assess and explore fossil datasets.

paleontology↗

bioRxiv2020

Epigenetic aging of classical monocytes from healthy individuals

The impact of healthy aging on molecular programming of immune cells is poorly understood. Here, we report comprehensive characterization of healthy aging in human classical monocytes, with a focus on epigenomic, transcriptomic, and proteomic alterations, as well as the corresponding proteomic and metabolomic data for plasma, using healthy cohorts of 20 young and 20 older individuals (~27 and ~64 years old on average). For each individual, we performed eRRBS-based DNA methylation profiling, which allowed us to identify a set of age-associated differentially methylated regions (DMRs) - a novel, cell-type specific signature of aging in DNA methylome. Optimized ultra-low-input ChIP-seq (ULI-ChIP-seq) data acquisition and analysis pipelines applied to 5 chromatin marks for each individual revealed lack of large-scale age-associated changes in chromatin modifications and allowed us to link hypo- and hypermethylated DMRs to distinct chromatin modification patterns. Specifically, hypermethylation events were associated with H3K27me3 in the CpG islands near promoters of lowly-expressed genes, while hypomethylated DMRs were enriched in H3K4me1 marked regions and associated with normal pattern of expression. Furthermore, hypo- and hypermethylated DMRs followed distinct functional and genetic association patterns. Hypomethylation events were associated with age-related increase of expression of the corresponding genes, providing a link between DNA methylation and age-associated transcriptional changes in primary human cells. Furthermore, these locations were also enriched in genetic regions associated by GWAS with asthma, total blood protein, hemoglobin levels and MS. On the other side, acceleration of epigenetic age in HIV and asthma stems only from changes in hypermethylated DMRs but not from hypomethylated loci.

systems biology↗

bioRxiv2020

Evolution leads to emergence: An analysis of protein interactomes across the tree of life

The internal workings of biological systems are notoriously difficult to understand. Due to the prevalence of noise and degeneracy in evolved systems, in many cases the workings of everything from gene regulatory networks to protein-protein interactome networks remain black boxes. One consequence of this black-box nature is that it is unclear at which scale to analyze biological systems to best understand their function. We analyzed the protein interactomes of over 1800 species, containing in total 8,782,166 protein-protein interactions, at different scales. We demonstrate the emergence of higher order macroscales in these interactomes and that these biological macroscales are associated with lower noise and degeneracy and therefore lower uncertainty. Moreover, the nodes in the interactomes that make up the macroscale are more resilient compared to nodes that do not participate in the macroscale. These effects are more pronounced in interactomes of Eukaryota, as compared to Prokaryota. This points to plausible evolutionary adaptation for macroscales: biological networks evolve informative macroscales to gain benefits of both being uncertain at lower scales to boost their resilience, and also being certain at higher scales to increase their effectiveness at information transmission. Our work explains some of the difficulty in understanding the workings of biological networks, since they are often most informative at a hidden higher scale, and demonstrates the tools to make these informative higher scales explicit.

systems biology↗

bioRxiv2020

A mouse SWATH-MS reference spectral library enables deconvolution of species-specific proteomic alterations in human tumour xenografts

SWATH-mass spectrometry (MS) enables accurate and reproducible proteomic profiling in multiple model organisms including the mouse. Here we present a comprehensive mouse reference spectral library (MouseRefSWATH) that permits quantification of up to 10,597 proteins (62.2% of the mouse proteome) by SWATH-MS. We exploit MouseRefSWATH to develop an analytical pipeline for species-specific deconvolution of proteomic alterations in human tumour xenografts (XenoSWATH). This method overcomes the challenge of high sequence similarity between mouse and human proteins, facilitating the study of host microenvironment-tumour interactions from bulk tumour measurements. We apply the XenoSWATH pipeline to characterise an intraductal xenograft model of breast ductal carcinoma in-situ and uncover complex regulation of cell migration pathways that are not restricted to tumour cells but also operate in the mouse stroma upon progression to invasive disease. MouseRefSWATH and XenoSWATH opens new opportunities for in-depth and reproducible proteomic assessment to address wide-ranging biological questions involving this important model organism.

biochemistry↗

bioRxiv2018

Effect of ring topology in a stochastic model for Z-ring dynamics in bacteria

Understanding the mechanisms responsible for dynamics of the Z-ring is important for our understanding of cell division in prokaryotic cells. In this work, we present a minimal stochastic model that qualititatively reproduces observations of polymerization, of formation of dynamic contractile ring that is stable for a long time and of depolymerization shown by FtsZ polymer. We explore different mechanisms for ring breaking and hydrolysis. Hydrolysis is known to regulate the dynamics of other tubulin polymers like microtubules. We find that the presence of the ring allows for an additional mechanism for regulating the dynamics of FtsZ polymers. Ring breaking dynamics in the presence of hydrolysis naturally induce rescue and catastrophe events, irrespective of the mechanism of hydrolysis. Based on our model, we conclude that the Z-ring undergoes random breaking and closing during the process of cell division.

biophysics↗

bioRxiv2017

Genome-wide and high-density CRISPR-Cas9 screens identify point mutations in PARP1 causing PARP inhibitor resistance

PARP inhibitors (PARPi) target homologous recombination defective tumour cells via synthetic lethality. Genome-wide and high-density CRISPR-Cas9 \"tag, mutate and enrich\" mutagenesis screens identified single amino acid mutations in PARP1 that cause profound PARPi-resistance. These included PARP1 mutations outside of the DNA interacting regions of the protein, such as mutations in solvent exposed regions of the catalytic domain and clusters of mutations around points of contact between ZnF, WGR and HD domains. These mutations altered PARP1 trapping, as did a mutation found in a clinical case of PARPi resistance. These genetic studies reinforce the importance of trapped PARP1 as a key cytotoxic DNA lesion and suggest that interactions between non-DNA binding domains of PARP1 influence cytotoxicity. Finally, different mechanisms of PARPi resistance (BRCA1 reversion, PARP1, 53BP1, REV7 mutation) had differing effects on chemotherapy sensitivity, suggesting that the underlying mechanism of PARPi resistance likely influences the success of subsequent therapies.

cancer biology↗