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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2018

Multi-context blind source separation by error-gated Hebbian rule

Animals need to adjust their inferences according to the context they are in. This is required for the multi-context blind source separation (BSS) task, where an agent needs to infer hidden sources from their context-dependent mixtures. The agent is expected to invert this mixing process for all contexts. Here, we show that a neural network that implements the error-gated Hebbian rule (EGHR) with sufficiently redundant sensory inputs can successfully learn this task. After training, the network can perform the multi-context BSS without further updating synapses, by retaining memories of all experienced contexts. Finally, if there is a common feature shared across contexts, the EGHR can extract it and generalize the task to even inexperienced contexts. This demonstrates an attractive use of the EGHR for dimensionality reduction by extracting common sources across contexts. The results highlight the utility of the EGHR as a model for perceptual adaptation in animals.

neuroscience↗

bioRxiv2018

Measuring the average power of neural oscillations

BackgroundNeural oscillations are often quantified as average power relative to a cognitive, perceptual, and/or behavioral task. This is commonly done using Fourier-based techniques, such as Welchs method for estimating the power spectral density, and/or by estimating narrowband oscillatory power across trials, conditions, and/or groups. The core assumption underlying these approaches is that the mean is an appropriate measure of central tendency. Despite the importance of this assumption, it has not been rigorously tested.\n\nNew methodWe introduce extensions of common approaches that are better suited for the physiological reality of how neural oscillations often manifest: as nonstationary, high-power bursts, rather than sustained rhythms. Log-transforming, or taking the median power, significantly reduces erroneously inflated power estimates.\n\nResultsAnalyzing 101 participants worth of human electrophysiology, totaling 3,560 channels and over 40 hours data, we show that, in all cases examined, spectral power is not Gaussian distributed. This is true even when oscillations are prominent and sustained, such as visual cortical alpha. Power across time, at every frequency, is characterized by a substantial long tail, which implies that estimates of average power are skewed toward large, infrequent high-power oscillatory bursts.\n\nComparison with existing methodsIn a simulated event-related experiment we show how introducing just a few high-power oscillatory bursts, as seen in real data, can, perhaps erroneously, cause significant differences between conditions using traditional methods. These erroneous effects are substantially reduced with our new methods.\n\nConclusionsThese results call into question the validity of common statistical practices in neural oscillation research.\n\nHighlightsO_LIAnalyses of oscillatory power often assume power is normally distributed.\nC_LIO_LIAnalyzing >40 hours of human M/EEG and ECoG, we show that in all cases it is not.\nC_LIO_LIThis effect is demonstrated in simple simulation of an event-related task.\nC_LIO_LIOverinflated power estimates are reduced via log-transformation or median power.\nC_LI

neuroscience↗

bioRxiv2018

Does the Diffusion Tensor Model Predict the Neurite Distribution of Cerebral Cortical Gray Matter? - Cortical DTI-NODDI

Diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) are widely used models to infer microstructural features in the brain from diffusion-weighted MRI. Several studies have recently applied both models to increase sensitivity to biological changes, however, it remains uncertain how these measures are associated. Here we show that cortical distributions of DTI and NODDI are associated depending on the choice of b-value, a factor reflecting strength of diffusion weighting gradient. We analyzed a combination of high, intermediate and low b-value data of multi-shell diffusion-weighted MRI (dMRI) in healthy 456 subjects of the Human Connectome Project using NODDI, DTI and a mathematical conversion from DTI to NODDI. Cortical distributions of DTI and DTI-derived NODDI metrics were remarkably associated with those in NODDI, particularly when applied highly diffusion-weighted data (b-value =3000 sec/mm2). This was supported by simulation analysis, which revealed that DTI-derived parameters with lower b-value datasets suffered from errors due to heterogeneity of cerebrospinal fluid fraction and partial volume. These findings suggest that high b-value DTI redundantly parallels with NODDI-based cortical neurite measures, but the conventional low b-value DTI does not reasonably characterize cortical microarchitecture.

neuroscience↗

bioRxiv2018

Role of RIG-I-like receptors in innate immune sensing of Coxsackievirus B3 and encephalomyocarditis virus in murine macrophages and fibroblasts

Viral infections are sensed by pattern recognition receptors that trigger an innate immune response through the expression of interferons (IFNs) and other cytokines. Most RNA viruses are sensed by the RIG-I like receptors (RLR)s. The contributions of these receptors to sensing viruses of the Picornaviridae family were investigated. Encephalomyocarditis virus (EMCV) and Coxsackievirus B3 (CVB3), picornaviruses of the Cardiovirus and Enterovirus genera, are detected by both MDA5 and RIG-I in bone marrow derived macrophages. In macrophages from wild type mice, type I IFN is produced early after infection; IFN{beta} synthesis is reduced in the absence of each sensor, while IFN production is reduced in the absence of MDA5. EMCV and CVB3 do not replicate in murine macrophages, and their detection is different in murine embryonic fibroblasts (MEFs), in which the viruses replicate to high titers. In MEFs RIG-I was essential for the expression of type I IFNs but contributes to increased yields of CVB3, while MDA5 inhibited CVB3 replication but in an IFN independent manner. These observations demonstrate that innate sensing of similar viruses by RLRs depends upon the cell type.\n\nImportanceEnteroviruses such as Coxsackieviruses are the most common human respiratory pathogens. The hosts innate immune response, in particular that modulated by the production of type I and III interferons, is thought to restrict picornavirus infection. Two cytoplasmic proteins, MDA5 and RIG-I, are critical for initiating the early innate immune response against these viruses. Mutations within MDA5 encoding gene have been associated with the development of severe enterovirus associated respiratory illnesses in healthy children. To further understand how the innate immune response dependent upon MDA5 and Rig-I is initiated during picornavirus infection, macrophages from mice lacking MDA5 or RIG-I were infected with Coxsackievirus B3 (CVB3) and a related animal virus. RIG-I is essential for type I IFN production during CVB3 infection; when MDA5 is present, viral titers are reduced by an IFN-independent pathway. These observations demonstrate that innate sensing of viruses by MDA5 and RIG-I depends upon the cell type.

microbiology↗

bioRxiv2018

In situ and high-resolution Cryo-EM structure of the Type VI secretion membrane complex

Bacteria have evolved macromolecular machineries that secrete effectors and toxins to survive and thrive in diverse environments. The type VI secretion system (T6SS) is a contractile machine that is related to Myoviridae phages. The T6SS is composed of a baseplate that contains a spike onto which an inner tube is built, surrounded by a contractile sheath. Unlike phages that are released to and act in the extracellular medium, the T6SS is an intracellular machine inserted in the bacterial membranes by a trans-envelope complex. This membrane complex (MC) comprises three proteins: TssJ, TssL and TssM. We previously reported the low-resolution negative stain electron microscopy structure of the enteroaggregative Escherichia coli MC and proposed a rotational 5-fold symmetry with a TssJ:TssL:TssM stoichiometry of 2:2:2. Here, cryo-electron tomography analysis of the T6SS MC confirmed the 5-fold symmetry in situ and identified the regions of the structure that insert into the bacterial membranes. A high resolution model obtained by single particle cryo-electron microscopy reveals its global architecture and highlights new features: five additional copies of TssJ, yielding a TssJ:TssL:TssM stoichiometry of 3:2:2, a 11-residue loop in TssM, protruding inside the lumen of the MC and constituting a functionally important periplasmic gate, and hinge regions. Based on these data, we revisit the model on the mechanism of action of the MC during T6SS assembly and function.

microbiology↗

bioRxiv2018

Stochastic simulations show how passive immunization can influence the germinal centre reaction and optimize host humoral responses

Passive immunization with antigen-specific antibodies was shown recently to induce lasting improvements in endogenous antibody production, raising the prospect of using passive immunization as a tool to engineer host humoral responses. The mechanism with which administered antibodies alter endogenous antibody production remains unknown. B cells that produce antigen-specific antibodies evolve and get selected in germinal centres (GCs). This selection requires that B cells acquire antigen presented in GCs. We hypothesized that passive immunization biases this selection in favour of B cells with high affinities for antigen. Administered antibodies form immune complexes with antigen which only B cells with higher affinities than the administered antibodies for antigen can rupture and acquire antigen, thus increasing the selection stringency in GCs. With this mechanistic hypothesis, we constructed a stochastic simulation model of the GC reaction. The simulations recapitulated and synthesized several independent experimental observations, presenting strong evidence in support of our hypothesis. Further, the simulations revealed a quality-quantity trade-off constraining the GC response. As the selection stringency increased, surviving B cells had higher affinities for antigen but fewer B cells survived. Increasing antigen availability in the GC relaxed this constraint. The affinity of the administered antibodies and/or antigen availability could thus be tuned to maximize the GC output. Comprehensively spanning parameter space, we predict passive immunization protocols that exploit the quality-quantity trade-off and maximize the GC output. Our study thus presents a new conceptual understanding of the GC reaction and a computational framework for the rational optimization of passive immunization strategies.\n\nSignificance statementWhen natural antibody production is inadequate, passive immunization with external antibodies can alleviate disease. Remarkably, passive immunization induced lasting improvements in natural antibody production in recent studies, suggesting that it could be deployed to engineer natural antibody responses. However, how administered antibodies alter natural antibody production remains unknown. B cells that produce antibodies targeting specific antigen evolve in germinal centres (GCs). We hypothesized that administered antibodies form complexes with antigen, preferentially allowing B cells with higher affinities to acquire antigen and be selected, thus altering antibody production. With this mechanistic hypothesis, we performed stochastic simulations of the GC reaction, which recapitulated experiments, unravelled a quality-quantity trade-off constraining the GC response, and predicted passive immunization protocols that maximized the GC output.

immunology↗

bioRxiv2018

Root volatiles in plant-plant interactions I: Characterization of root sesquiterpene emissions from Centaurea stoebe and their effects on other plants

Volatile organic compounds (VOCs) emitted by plant leaves can influence the physiology of neighboring plants. In contrast to interactions above ground, little is known about the role of VOCs in belowground plant-plant interactions. Here, we characterize constitutive root volatile emissions of the spotted knapweed (Centaurea stoebe) and explore the impact of these volatiles on the germination and growth of different sympatric plant species. We show that C. stoebe roots emit high amounts of sesquiterpenes, with estimated release rates of (E)-{beta}-caryophyllene above 3 g g-1 dw h-1. Sesquiterpene emissions show little variation between different C. stoebe populations, but vary substantially between different Centaurea species. Through root transcriptome sequencing, we identify six root-expressed sesquiterpene synthases (TPSs). Two root-specific TPSs, CsTPS4 and CsTPS5, are sufficient to produce the full blend of emitted root sesquiterpenes. Volatile exposure experiments demonstrate that C. stoebe root volatiles have neutral to positive effects on the germination and growth of different sympatric neighbors. Thus, constitutive root sesquiterpenes produced by two C. stoebe TPSs are associated with facilitation of sympatric neighboring plants. The release of root VOCs may thus influence C. stoebe abundance and plant community structure in nature.

plant biology↗

bioRxiv2018

Defoliation estimation of forest trees from ground-level images

In this paper, we propose to estimate tree defoliation from ground-level RGB photos with convolutional neural networks (CNN). Tree defoliation is usually assessed with field campaigns, where experts estimate multiple tree health indicators per sample site. Campaigns span entire countries to come up with a holistic, nation-wide picture of forest health. Surveys are very laborious, expensive, time-consuming and need a large number of experts. We aim at making the monitoring process more efficient by casting tree defoliation estimation as an image interpretation problem. What makes this task challenging is strong variance in lighting, viewpoint, scale, tree species, and defoliation types. Instead of accounting for each factor separately through explicit modelling, we learn a joint distribution directly from a large set of annotated training images following the end-to-end learning paradigm of deep learning. The proposed workflow works as follows: (i) Human experts visit individual trees in forests distributed all over Switzerland, (ii) acquire one photo per tree with an off-the-shelf, hand-held RGB camera and (iii) assign a defoliation value. The CNN approach is (iv) trained on a subset of the images with expert defoliation assessments and (v) tested on a hold-out part to check predicted values against ground truth. We evaluate our supervised method on three data sets with different level of difficulty acquired in Swiss forests and achieve an average mean absolute error (avgMAE) of 7.6% for the joint data set after cross-validation. Comparison to a group of human experts on one of the data sets shows that our CNN approach performs only 0.9 percent points worse. We show that tree defoliation estimation from ground-level RGB images with a CNN works well and achieves performance close to human experts.

ecology↗

bioRxiv2018

Fast Detection of Differential Chromatin Domains with SCIDDO

The generation of genome-wide maps of histone modifications using chromatin immunoprecipitation sequencing (ChIP-seq) is a common approach to dissect the complexity of the epigenome. However, interpretation and differential analysis of histone ChIP-seq datasets remains challenging due to the genomic co-occurrence of several marks and their difference in genomic spread. Here we present SCIDDO, a fast statistical method for the detection of differential chromatin domains (DCDs) from chromatin state maps. DCD detection simplifies relevant tasks such as the characterization of chromatin changes in differentially expressed genes or the examination of chromatin dynamics at regulatory elements. SCIDDO is available at github.com/ptrebert/sciddo

bioinformatics↗

bioRxiv2018

A haplotype-resolved draft genome of the European sardine (Sardina pilchardus)

BackgroundThe European sardine (Sardina pilchardus Walbaum, 1792) has a high cultural and economic importance throughout its distribution. Monitoring studies of sardine populations report an alarming decrease in stocks due to overfishing and environmental change, which has resulted in historically low captures along the Iberian Atlantic coast. Consequently, there is an urgent need to better understand the causal factors of this continuing decrease in the sardine stock. Important biological and ecological features such as levels of population diversity, structure, and migratory patterns can be addressed with the development and use of genomics resources.\n\nFindingsThe sardine genome of a single female individual was sequenced using Illumina HiSeq X Ten 10X Genomics linked-reads generating 113.8 Gb of data. Three draft genomes were assembled: two haploid genomes with a total size of 935 Mbp (N50 103Kb) each, and a consensus genome with a total size of 950 Mbp (N50 97Kb). The genome completeness assessment captured 84% of Actinopterygii Benchmarking Universal Single-Copy Orthologs. To obtain a more complete analysis, the transcriptomes of eleven tissues were sequenced and used to aid the functional annotation of the genome, resulting in 40 777 genes predicted. Variant calling on nearly half of the haplotype genome resulted in the identification of more than 2.3 million phased SNPs with heterozygous loci.\n\nConclusionsA draft genome was obtained with the 10X Genomics linked-reads technology, despite a high level of sequence repeats and heterozygosity that are expected genome characteristics of a wild sardine. The reference sardine genome and respective variant data are a cornerstone resource of ongoing population genomics studies to be integrated into future sardine stock assessment modelling to better manage this valuable resource.

genomics↗

bioRxiv2018

Root volatiles in plant-plant interactions II: Root terpenes from Centaurea stoebe modify Taraxacum officinale root chemistry and root herbivore growth

Volatile organic compounds (VOCs) emitted by plant roots can influence the germination and growth of neighboring plants. However, little is known about the effects of root VOCs on plant-herbivore interactions. The spotted knapeed (Centaurea stoebe) constitutively releases high amounts of sesquiterpenes into the rhizosphere. Here, we examine the impact of C. stoebe root VOCs on primary and secondary metabolites of sympatric Taraxacum officinale plants and the resulting plant-mediated effects on a generalist root herbivore, the white grub Melolontha melolontha. We show that exposure of T. officinale to C. stoebe root VOCs does not affect the accumulation of defensive secondary metabolites, but modulates carbohydrate and total protein levels in T. officinale roots. Furthermore, VOC exposure increases M. melolontha growth on T. officinale plants. Exposure of T. officinale to a major C. stoebe root VOC, the sesquiterpene (E)-{beta}-caryophyllene, partially mimics the effect of the full root VOC blend on M. melolontha growth. Thus, releasing root VOCs can modify plant-herbivore interactions of neighboring plants. The release of VOCs to increase the susceptibility of other plants may be a form of plant offense.

plant biology↗

bioRxiv2018

Modelling double strand break susceptibility to interrogate structural variation in cancer

BackgroundStructural variants (SVs) are known to play important roles in a variety of cancers, but their origins and functional consequences are still poorly understood. Many SVs are thought to emerge via errors in the repair processes following DNA double strand breaks (DSBs) and previous studies have experimentally measured DSB frequencies across the genome in cell lines.\n\nResultsUsing these data we derive the first quantitative genome-wide models of DSB susceptibility, based upon underlying chromatin and sequence features. These models are accurate and provide novel insights into the mutational mechanisms generating DSBs. Models trained in one cell type can be successfully applied to others, but a substantial proportion of DSBs appear to reflect cell type specific processes. Using model predictions as a proxy for susceptibility to DSBs in tumours, many SV enriched regions appear to be poorly explained by selectively neutral mutational bias alone. A substantial number of these regions show unexpectedly high SV breakpoint frequencies given their predicted susceptibility to mutation, and are therefore credible targets of positive selection in tumours. These putatively positively selected SV hotspots are enriched for genes previously shown to be oncogenic. In contrast, several hundred regions across the genome show unexpectedly low levels of SVs, given their relatively high susceptibility to mutation. These novel coldspot regions appear to be subject to purifying selection in tumours and are enriched for active promoters and enhancers.\n\nConclusionsWe conclude that models of DSB susceptibility offer a rigorous approach to the inference of SVs putatively subject to selection in tumours.

bioinformatics↗

bioRxiv2018

Spatial relationships between white matter degeneration, amyloid load and cortical volume in amnestic mild cognitive impairment

The spatial-temporal relationships between gray and white matter (WM) degeneration during preclinical and early symptomatic Alzheimers disease are poorly understood. We characterized {beta}-amyloid deposition, cortical volume and WM degeneration in 44 subjects including healthy control (N=23), amnestic mild cognitive impairment (aMCI) (N=19), and early Alzheimers subjects (N=2). Integrated PET-MRI provided simultaneous measurement of 18F-Florbetapir uptake in cortical areas, regional brain volumes from structural MRI, and WM tract integrity metrics from diffusion MRI using biophysical modeling.\n\nAcross the cohort of healthy control and aMCIs, cortical volumes correlated poorly with {beta}-amyloid deposition in the same area (p < 0.05 only in the posterior cingulate and parietal lobe). WM degeneration correlated significantly with both amyloid and volume of connected cortical areas, but more strongly with volume. Diffusion MRI metrics for WM demyelination and/or axonal loss could therefore provide new biomarkers associated with clinical Alzheimers conversion. These WM changes may represent sequential propagation of Alzheimers neurodegeneration between functionally connected regions, and/or evidence of direct WM injury during the Alzheimers pathology cascade.

neuroscience↗

bioRxiv2018

Metabolomic signature of angiopoietin-like protein 3 deficiency in fasting and postprandial state

ObjectiveLoss-of-function variants in the angiopoietin-like 3 gene (ANGPTL3) have been associated with low levels of plasma lipoproteins and decreased coronary artery disease risk. We aimed to determine detailed metabolic effects of genetically-induced ANGPTL3 deficiency in fasting and postprandial state.\n\nApproach and ResultsWe studied individuals carrying S17X loss-of-function mutation in ANGPTL3 (6 homozygous and 32 heterozygous carriers) and 38 noncarriers. Nuclear magnetic resonance metabolomics was used to quantify 225 circulating metabolic measures. We compared metabolic differences between loss-of-function carriers and noncarriers in fasting state and after a high fat meal. In fasting, ANGPTL3 deficiency was characterized by similar extent of reductions in low-density lipoprotein cholesterol (0.74 SD-units lower concentration per loss-of-function allele [95%CI 0.42-1.06]) as observed for many triglyceride-rich lipoprotein measures, including very-low-density lipoprotein cholesterol (0.75 [0.45-1.05]). Within most lipoprotein subclasses, absolute levels of cholesterol were decreased more than triglycerides, resulting in the relative proportion of cholesterol being reduced within triglyceride-rich lipoproteins and their remnants. Further, beta-hydroxybutyrate was elevated (0.55 [0.21-0.89]). Homozygous ANGPTL3 loss-of-function carriers showed essentially no postprandial increase in triglyceride-rich lipoproteins and fatty acids, without evidence for adverse compensatory metabolic effects.\n\nConclusionsIn addition to overall triglyceride and low-density lipoprotein cholesterol lowering effects, ANGPTL3 deficiency results in reduction of cholesterol proportion within triglyceride-rich lipoproteins and their remnants. Further, ANGPTL3 loss-of-function carriers had elevated ketone body production, suggesting enhanced hepatic fatty acid beta-oxidation. The detailed metabolic profile in human knockouts of ANGPTL3 reinforces inactivation of ANGPTL3 as a promising therapeutic target for decreasing cardiovascular risk.\n\nHIGHLIGHTSO_LIANGPTL3 deficiency results in similar reductions in LDL cholesterol and many triglyceride-rich lipoprotein lipids measures, such as VLDL cholesterol, with no evidence of substantial adverse effects on the comprehensive panel of circulating metabolite biomarkers tested here.\nC_LIO_LIIn particular, ANGPTL3 deficiency results in reduction of cholesterol content in triglyceride-rich lipoproteins and their remnants, which have been highlighted as risk factor for cardiovascular disease independently of LDL levels.\nC_LIO_LIHomozygous ANGPTL3 loss-of-function carriers show essentially no postprandial increase in triglyceride-rich lipoproteins and fatty acids in response to a fat challenge, and display consistently elevated postprandial levels of ketone bodies and lactate when compared to noncarriers, suggesting enhanced hepatic fatty acid beta-oxidation.\nC_LI

genetics↗

bioRxiv2018

Anthropogenic remediation of heavy metals selects against natural microbial remediation

In an era of unprecedented environmental change, there have been increasing ecological and global public health concerns associated with exposure to anthropogenic pollutants. While there is a pressing need to remediate polluted ecosystems, human intervention strategies might unwittingly oppose selection for natural detoxification, which is primarily carried out by microbes. We test this possibility in the context of a ubiquitous chemical remediation strategy aimed at targeting toxic metal pollution: the addition of lime-containing materials. Here we show that raising pH by liming decreased the availability of toxic metals in acidic mine-degraded soils, but as a consequence selected against microbial taxa that naturally remediate soil through the production of metal-scavenging siderophores. Understanding the ecological and evolutionary consequences of human intervention on key traits is crucial for the engineering of evolutionary resilient microbial communities, having important implications for human health and biotechnology.

ecology↗

bioRxiv2018

Immunoinformatics Prediction of Epitope Based Peptide Vaccine Against Madurella mycetomatis Translationally Controlled Tumor Protein

BackgroundMadurella. mycetomatis is most common causative agent of mycetoma in Sudan and worldwide. No vaccines are available till now so design of effective vaccine is essential as protection tool. Peptide vaccine can overcome the common side effects of the conventional vaccines. The aim of this study was to design peptide based vaccine for M.Mycetomatis Translationally Controlled Tumor Protein (TCTP) using immunoinformatics tools.\n\nMaterials and methodsTCTP sequences were retrieved from NCBI and then processed using BioEdit program to determine conserved regions and different immunoinformatics tools from IEDB. Population coverage analysis was performed for the most promising epitopes. Homology modelling was performed to show their structural positions in TCTP. Protein analysis was done using Expasy (ProtParamsotware).\n\nResults and conclusionFour epitopes passed the Bepipred, Emini, Kolaskar and Tongaonkar tools. 111 epitopes were predicted to interact with MHCI alleles with IC50 < 500 nM, three of them were most promising. 274 predicted epitopes were interacted with MHCII alleles with IC50 < 100 nM, four of them were most promising. The epitope (YMKSVKKAL) was the most promising one concerning its binding with MHCI alleles, while (FRLQSTSFD) was the most promising for MHC II. The epitope (YLKAYMKSV) is shared betweenMHC I and II. For the population coverage of M. Mycetomatis TCTP vaccine Sudan (90.39%) had the highest percentage for MHC I. This is the first computational vaccinology study conducted in mycetoma caused by M. Mycetomatis using TCTP.

bioinformatics↗

bioRxiv2018

Comparative genomics of human Lactobacillus crispatus isolates reveals genes for glycosylation and glycogen degradation: Implications for in vivo dominance of the vaginal microbiota

BackgroundA vaginal microbiota dominated by lactobacilli (particularly Lactobacillus crispatus) is associated with vaginal health, whereas a vaginal microbiota not dominated by lactobacilli is considered dysbiotic. Here we investigated whether L. crispatus strains isolated from the vaginal tract of women with Lactobacillus-dominated vaginal microbiota (LVM) are pheno- or genotypically distinct from L. crispatus strains isolated from vaginal samples with dysbiotic vaginal microbiota (DVM).\n\nResultsWe studied 33 L. crispatus strains (n=16 from LVM; n=17 from DVM). Comparison of these two groups of strains showed that, although strain differences existed, both groups were heterofermentative, produced similar amounts of organic acids, inhibited Neisseria gonorrhoeae growth and did not produce biofilms. Comparative genomics analyses of 28 strains (n=12 LVM; n=16 DVM) revealed a novel, 3-fragmented glycosyltransferase gene that was more prevalent among strains isolated from DVM. Most L. crispatus strains showed growth on glycogen-supplemented growth media. Strains that showed less efficient (n=6) or no (n=1) growth on glycogen all carried N-terminal deletions (respectively, 29 and 37 amino acid-deletions) in a putative pullulanase type I gene.\n\nDiscussionL. crispatus strains isolated from LVM were not phenotypically distinct from L. crispatus strains isolated from DVM, however, the finding that the latter were more likely to carry a 3-fragmented glycosyltransferase gene may indicate a role for cell surface glycoconjugates, which may shape vaginal microbiota-host interactions. Furthermore, the observation that variation in the pullulanase type I gene associated with growth on glycogen discourages previous claims that L. crispatus cannot directly utilize glycogen.

microbiology↗

bioRxiv2018

Principles of Meiotic Chromosome Assembly

During meiotic prophase, chromosomes organise into a series of chromatin loops emanating from a proteinaceous axis, but the mechanisms of assembly remain unclear. Here we elucidate how this elaborate three-dimensional chromosome organisation is underpinned by genomic sequence in Saccharomyces cerevisiae. Entering meiosis, strong cohesin-dependent grid-like Hi-C interaction patterns emerge, reminiscent of mammalian interphase organisation, but with distinct regulation. Meiotic patterns agree with simulations of loop extrusion limited by barriers, yet are patterned by convergent transcription rather than binding of the mammalian interphase factor, CTCF, which is absent in S. cerevisiae--thereby both challenging and extending current paradigms of local chromosome organisation. While grid-like interactions emerge independently of meiotic chromosome synapsis, synapsis itself generates additional compaction that matures differentially according to telomere proximity and chromosome size. Collectively, our results elucidate fundamental principles of chromosome assembly and demonstrate the essential role of cohesin within this evolutionarily conserved process.

molecular biology↗