Biology subjects

Wang, B.

Publications and source records attributed to Wang, B..

At least 649 records · Page 36Linked to original sources

bioRxiv2020

ICOS enhances follicular T helper responses and deteriorates the pathogenic process of liver in mice infected with Schistosoma japonicum

BackgroundHumoral immune responses play an important role in mediating liver granulomatous inflammation and fibrosis in schistosomiasis. Follicular helper T (Tfh) cells have a central role in mediating humoral immune responses. Generation of Tfh cells depends on inducible T cell costimulator (ICOS) signaling, but the underlying molecular mechanisms are incompletely understood in pathogenesis of schistosomiasis. Methodology/Principal FindingsWe used a strain of ICOS-transgenic (Tg) mice to test the degrees of liver granulomatous inflammation and fibrosis, the frequency of splenic Tfh cells and soluble egg antigen-specific cytokine responses longitudinally in mice following Schistosoma japonicum (S. japonicum) infection. In comparison with that in wide-type (WT) mice, significantly severer liver granulomatous inflammation and fibrosis and higher mortality were observed in ICOS-Tg mice. Significantly higher frequency of splenic Tfh cells was accompanied by significantly higher levels of Bcl-6 and CXCR5 expression in the livers of ICOS-Tg mice. Furthermore, significantly higher levels of SEA-specific IL-4, IL-6, IL-10, IL-13, IL-17A, IL-21 and TGF-{beta}1 responses, but lower levels of IFN-{gamma} responses were detected in ICOS-Tg mice, which were abrogated by treatment with ICOS blockers in vitro. In addition, significantly higher levels of serum anti-SEA IgG were detected in ICOS-Tg mice. Conclusions/SignificanceThe ICOS-related signaling may promote the pathogenesis of murine schistosomiasis by polarizing Tfh cells, which may be immune check points for the prevention and intervention of schistosomiasis. Author summaryGranulomatous inflammation and fibrosis in the liver are the major pathogenic characteristics of schistosomiasis. ICOS is crucial for the development of Tfh cells, which are the key modulators of B cell activation and humoral immunity. However, the underlying molecular mechanisms are incompletely understood in pathogenesis of schistosomiasis. Here, our results showed that the ICOS over-expression would significantly induce severer liver inflammation and fibrosis, higher frequency of splenic Tfh, higher levels of anti-SEA IgG as well as imbalanced SEA-specific cytokine responses in ICOS-Tg mice. The findings suggested that ICOS signaling may promote the pathogenesis of murine schistosoma-related liver inflammation and fibrosis by polarizing Tfh cells. Potentially, ICOS signaling and Tfh cells may be immune check points for the prevention and intervention of schistosomiasis.

immunology↗

bioRxiv2020

A non-canonical histone acetyltransferase targets intragenic enhancers and regulates plant architecture

Axillary meristem development determines both plant architecture and crop yield; this critical process is regulated by the TCP transcription factor (TF) family, including the maize TB1 and Arabidopsis BRC1. Studies have shown that both TB1 and AtBRC1 can target the gene body regions of some target genes and activate their expression; however, the regulatory mechanisms remain largely unknown. Here, we show that a cucumber CYC/TB1 homologue, TEN, controls the identity and mobility of tendrils. Through its C-terminus, TEN binds at intragenic enhancers of target genes; its N-terminal domain functions as a novel, non-canonical histone acetyltransferase (HAT) to preferentially act on lysine 56 and 122, of the histone H3 globular domain. This HAT activity is responsible for chromatin loosening and host gene activation. The N-termini of all tested CYC/TB1-like proteins contain an intrinsically disordered region (IDR), and despite their sequence divergence, they have conserved HAT activity. This study discovered a non-canonical class of HATs, and as well, provides a mechanism by which modification at the H3 globular domain is integrated with the transcription process.

plant biology↗

bioRxiv2020

Genome-scale metabolic rewiring to achieve predictable titers rates and yield of a non-native product at scale

Achieving high titer rates and yields (TRY) remains a bottleneck in the production of heterologous products through microbial systems, requiring elaborate engineering and many iterations. Reliable scaling of engineered strains is also rarely addressed in the first designs of the engineered strains. Both high TRY and scale are challenging metrics to achieve due to the inherent trade-off between cellular use of carbon towards growth vs. target metabolite production. We hypothesized that being able to strongly couple product formation with growth may lead to improvements across both metrics. In this study, we use elementary mode analysis to predict metabolic reactions that could be targeted to couple the production of indigoidine, a sustainable pigment, with the growth of the chosen host, Pseudomonas putida KT2440. We then filtered the set of 16 predicted reactions using -omics data. We implemented a total of 14 gene knockdowns using a CRISPRi method optimized for P. putida and show that the resulting engineered P. putida strain could achieve high TRY. The engineered pairing of product formation with carbon use also shifted production from stationary to exponential phase and the high TRY phenotype was maintained across scale. In one design cycle, we constructed an engineered P. putida strain that demonstrates close to 50% maximum theoretical yield (0.33 g indigoidine/g glucose consumed), reaching 25.6 g/L indigoidine and a rate of 0.22g/l/h in exponential phase. These desirable phenotypes were maintained from batch to fed-batch cultivation mode, and from 100ml shake flasks to 250 mL ambr(R) and 2 L bioreactors.

bioengineering↗

bioRxiv2020

Pharmacologic activation of the mitochondrial phosphoenolpyruvate cycleenhances islet function in vivo

The mitochondrial GTP (mtGTP)-dependent phosphoenolpyruvate (PEP) cycle is an anaplerotic-cataplerotic mitochondrial shuttle utilizing mitochondrial PEPCK (PCK2) and pyruvate kinase (PK). PEP cycling stimulates insulin secretion via OxPhos-independent lowering of ADP by PK. We assess in vivo whether islet PCK2 is necessary for glucose sensing and if speeding the PEP cycle via pharmacological PK activators amplifies insulin secretion. Pck2-/- mice had severely impaired insulin secretion during islet perifusion, oral glucose tolerance tests and hyperglycemic clamps. Acute and chronic pharmacologic PK activator therapy improved islet insulin secretion from normal, high-fat diet (HFD) fed, or Zucker diabetic fatty (ZDF) rats, and glucolipotoxic or diabetic humans. A similar improvement in insulin secretion was observed in regular chow and HFD rats in vivo. Insulin secretion and cytosolic Ca2+ during PK activation were dependent on PCK2. These data provide a preclinical rationale for strategies, such as PK activation, that target the PEP cycle to improve glucose homeostasis. HighlightsO_LILoss of mitochondrial phosphoenolpyruvate (PEP) impairs insulin release in vivo. C_LIO_LIPyruvate kinase (PK) activators stimulate beta-cells in preclinical diabetes models. C_LIO_LIPEP cycling in vivo depends on PK and mitochondrial PEPCK (PCK2) for insulin release. C_LIO_LIAcute and 3-week oral PK activator amplifies insulin release during hyperglycemia. C_LI eTOC BlurbAbudukadier et al. show that small molecule pyruvate kinase activation in vivo and in vitro increases insulin secretion in rodent and human models of diabetes. The phosphoenolpyruvate (PEP) cycling mechanism and its amplification are dependent on mitochondrial PEPCK (PCK2).

physiology↗

bioRxiv2020

Harmonic-Balance Circuit Analysis for Electro-Neural Interfaces

ObjectiveAvoidance of the adverse electrochemical reactions at the electrode-electrolyte interface defines the voltage safety window and limits the charge injection capacity (CIC) of an electrode material. For an electrode that is not ideally capacitive, the CIC depends on the waveform of the stimulus. We study the modeling of the charge injection dynamics to optimize the waveforms for efficient neural stimulation within the electrochemical safety limits. ApproachThe charge injection dynamics at the electrode-electrolyte interface is typically characterized by the electrochemical impedance spectrum, and is often approximated by discrete-element circuit models. We compare the modeling of the complete circuit, including a non-linear driver such as a photodiode, based on the harmonic-balance (HB) analysis with the analysis based on various discrete element approximations. To validate the modeling results, we performed experiments with iridium-oxide electrodes driven by a current source with diodes in parallel, which mimics a photovoltaic circuit. Main resultsApplication of HB analysis based on a full impedance spectrum in frequency domain eliminates the complication of finding the discrete-element circuit model in traditional approaches. HB-based results agree with the experimental data better than the discrete-element circuit analysis. HB technique can be applied not only to demonstrate the circuit response to periodic stimulation, but also to describe the initial transient behavior when a burst waveform is applied. SignificanceHB-based circuit analysis accurately describes the dynamics of electrode-electrolyte interfaces and driving circuits for all pulsing schemes. This allows optimizing the stimulus waveform to maximize the CIC, based on the impedance spectrum alone.

bioengineering↗

bioRxiv2020

A Whole-Brain Regression Method to Identify Individual and Group Variations in Functional Connectivity

Resting-state functional connectivity is an important and widely used measure of individual and group differences. These differences are typically attributed to various demographic and/or clinical factors. Yet, extant statistical methods are limited to linking covariates with variations in functional connectivity across subjects, especially at the voxel-wise level of the whole brain. This paper introduces a generalized linear model method that regresses whole-brain functional connectivity on covariates. Our approach builds on two methodological components. We first employ whole-brain group ICA to reduce the dimensionality of functional connectivity matrices, and then search for matrix variations associated with covariates using covariate assisted principal regression, a recently introduced covariance matrix regression method. We demonstrate the efficacy of this approach using a resting-state fMRI dataset of a medium-sized cohort of subjects obtained from the Human Connectome Project. The results show that the approach enjoys improved statistical power in detecting interaction effects of sex and alcohol on whole-brain functional connectivity, and in identifying the brain areas contributing significantly to the covariate-related differences in functional connectivity.

neuroscience↗

bioRxiv2020

Deep Learning Identifies Cardiomyocyte Nuclei in Murine Tissue with High Precision

Proper identification and annotation of cells in mammalian tissues is of paramount importance to biological research. Various approaches are currently used to identify and label cell types of interest in complex tissues. In this report, we generated an artificial intelligence (AI) deep learning model that uses image segmentation to predict cardiomyocyte nuclei in mouse heart sections without a specific cardiomyocyte nuclear label. This tool can annotate cardiomyocytes highly sensitively and specifically (AUC 0.94) using only cardiomyocyte structural protein immunostaining and a global nuclear stain. We speculate that our method is generalizable to other tissues to annotate specific cell types and organelles in a label-free way.

cell biology↗

bioRxiv2020

Myosin X interaction with KIF13B, a crucial pathway for Netrin-1-induced axonal development

Myosin X (Myo X) transports cargos to the tip of filopodia for cell adhesion, migration, and neuronal axon guidance. Deleted in Colorectal Cancer (DCC) is one of Myo X cargos essential for Netrin-1-regulated axon pathfinding. Myo Xs function in axon development in vivo and the underlying mechanisms remain poorly understood. Here, we provide evidence for Myo Xs function in Netrin-1-DCC regulated axon development in mouse neocortex. Knocking-out (KO) or knocking-down (KD) Myo X in embryonic cortical neurons impairs axon initiation and contralateral branching/targeting. Similar axon deficits are detected in Netrin-1-KO or DCC-KD cortical neurons. Myo X interacts with KIF13B (a kinesin family motor protein), which is induced by Netrin-1. Netrin-1 promotes anterograde transportation of Myo X into axons in KIF13B dependent manner. KIF13B-KD cortical neurons exhibit similar axon deficits. These results suggest Myo X-KIF13B as a critical pathway for Netrin-1 promoted axon initiation and branching/targeting.

developmental biology↗

bioRxiv2020

EZcalcium: Open Source Toolbox for Analysis of Calcium Imaging Data

Fluorescence calcium imaging using a range of microscopy approaches, such as 2-photon excitation or head-mounted miniscopes, is one of the preferred methods to record neuronal activity and glial signals in various experimental settings, including acute brain slices, brain organoids, and behaving animals. Because changes in the fluorescence intensity of genetically encoded or chemical calcium indicators correlate with action potential firing in neurons, data analysis is based on inferring such spiking from changes in pixel intensity values across time within different regions of interest. However, the algorithms necessary to extract biologically relevant information from these fluorescent signals are complex and require significant expertise in programming to develop robust analysis pipelines. For decades, the only way to perform these analyses was for individual laboratories to write their own custom code. These routines were typically not well annotated and lacked intuitive graphical user interfaces (GUIs), which made it difficult for scientists in other laboratories to adopt them. Although the panorama is changing with recent tools like CaImAn, Suite2P and others, there is still a barrier for many laboratories to adopt these packages, especially for potential users without sophisticated programming skills. As 2-photon microscopes are becoming increasingly affordable, the bottleneck is no longer the hardware, but the software used to analyze the calcium data in an optimal manner and consistently across different groups. We addressed this unmet need by incorporating recent software solutions for motion correction, segmentation, signal extraction and deconvolution of calcium imaging data into an open-source, easy to use, GUI-based, intuitive and automated data analysis software, which we named EZcalcium.

neuroscience↗

bioRxiv2019

Genome-wide CRISPR screens identify essential cell growth mediators in BRAF-inhibitor resistant melanoma

BRAF is a serine-threonine kinase that harbors activating mutations in [~]7% of human malignancies and [~]60% of melanomas. Despite initial clinical responses to BRAF inhibitors (BRAFi), patients frequently develop drug resistance. To identify candidate therapeutic targets for BRAFi-resistant melanoma, we conducted CRISPR screens in melanoma cells harboring an activating BRAF mutation that had also acquired resistance to BRAFi. The screens identified pathways and genes critical for BRAFi resistance in melanoma cells. To investigate the mechanisms and pathways enabling resistance to BRAFi in melanomas, we integrated expression data, ATAC-seq, and CRISPR screen results. We identified the JUN family of transcription factors and the ETS family transcription factor ETV5 as key regulators of CDK6 that enabled resistance to BRAFi in melanoma cells. Our findings reveal genes whose loss of function conferred resistance to a selective BRAF inhibitor, providing new insight into signaling pathways that contribute to acquired resistance in melanoma.

cancer biology↗

bioRxiv2019

Neural Encoding for Human Visual Cortex with Deep Neural Networks Learning "What" and "Where"

Neural encoding, a crucial aspect to understand human brain information processing system, aims to establish a quantitative relationship between the stimuli and the evoked brain activities. In the field of visual neuroscience, with the ability to explain how neurons in primary visual cortex work, population receptive field (pRF) models have enjoyed high popularity and made reliable progress in recent years. However, existing models rely on either the inflexible prior assumptions about pRF or the clumsy parameter estimation methods, severely limiting the expressiveness and interpretability. In this paper, we propose a novel neural encoding framework by learning "what" and "where" with deep neural networks. The modeling approach involves two separate aspects: the spatial characteristic ("where") and feature selection ("what") of neuron populations in visual cortex. Specifically, we use the receptive field estimation and multiple features regression to learn these two aspects respectively, which are implemented simultaneously in a deep neural network. The two forms of regularizations: sparsity and smoothness, are also adopted in our modeling approach, so that the receptive field can be estimated automatically without prior assumptions about shapes. Furthermore, an attempt is made to extend the voxel-wise modeling approach to multi-voxel joint encoding models, and we show that it is conducive to rescuing voxels with poor signal-to-noise characteristics. Extensive empirical results demonstrate that the method developed herein provides an effective strategy to establish neural encoding for human visual cortex, with the weaker prior constraints but the higher encoding performance. Author summaryCharacterizing the quantitative relationship between the stimuli and the evoked brain activities usually involves learning the spatial characteristic ("where") and feature selection ("what") of neuron populations. As an effective strategy, we propose a novel end-to-end "what" and "where" architecture to perform neural encoding. The proposed modeling approach consists of receptive field estimation and multiple features regression, which learns "where" and "what" simultaneously in a deep neural network. Different from previous methods, we use the sparsity and smoothness regularizations in the deep neural network to guide the receptive field estimation, so that the receptive field for each voxel can be estimated automatically. Moreover, in consideration of computational similarities between adjacent voxels, we made an attempt to extend the proposed modeling approach to multi-voxel joint encoding models, improving the encoding performance of voxels with poor signal-to-noise characteristics. Empirical evaluations show that the proposed method outperforms other baselines to achieve the state-of-the-art performance.

neuroscience↗

bioRxiv2019

Profiling of chromatin accessibility across Aspergillus species and identification of transcription factor binding sites in the Aspergillus genome using filamentous fungi ATAC-seq

To identify cis-regulatory elements (CREs) and motifs of TF binding is an important step in understanding the regulatory functions of TF binding and gene expression. The lack of experimentally determined and computationally inferred data means that the genome-wide CREs and TF binding sites (TFBs) in filamentous fungi remain unknown. ATAC-seq is a technique that provides a high-resolution measurement of chromatin accessibility to Tn5 transposase integration. In filamentous fungi, the existence of cell walls and the difficulty in purifying nuclei have prevented the routine application of this technique. Herein, we modified the ATAC-seq protocol in filamentous fungi to identify and map open chromatin and TF-binding sites on a genome-scale. We applied the assay for ATAC-seq among different Aspergillus species, during different culture conditions, and among TF-deficient strains to delineate open chromatin regions and TFBs across each genome. The syntenic orthologues regions and differential changes regions of chromatin accessibility were responsible for functional conservative regulatory elements and differential gene expression in the Aspergillus genome respectively. Importantly, 17 and 15 novel transcription factor binding motifs that were enriched in the genomic footprints identified from ATAC-seq data of A. niger, were verified in vivo by our artificial synthetic minimal promoter system, respectively. Furthermore, we first confirmed the strand-specific patterns of Tn5 transposase around the binding sites of known TFs by comparing ATAC-seq data of TF-deficient strains with the data from a wild-type strain.

genomics↗

bioRxiv2019

Cis-regulatory analysis of Onecut1 expression in fate-restricted retinal progenitor cells

BackgroundThe vertebrate retina consists of six major classes of neuronal cells. During development, these cells are generated from a pool of multipotent retinal progenitor cells (RPCs) that express the gene Vsx2. Fate-restricted RPCs have recently been identified, with limited mitotic potential and cell fate possibilities compared to multipotent RPCs. One population of fate-restricted RPCs, marked by activity of the regulatory element ThrbCRM1, gives rise to both cone photoreceptors and horizontal cells. These cells do not express Vsx2, but co-express the transcription factors (TFs) Onecut1 and Otx2, which bind to ThrbCRM1. The components of the gene regulatory networks that control the transition from multipotent to fate-restricted gene expression are not known. This work aims to identify and evaluate cis-regulatory elements proximal to Onecut1 to identify the gene regulatory networks involved in RPC fate-restriction. MethodWe identified regulatory elements through ATAC-seq and conservation, followed by reporter assays to screen for activity based on temporal and spatial criteria. The regulatory elements of interest were subject to deletion and mutation analysis to identify functional sequences and evaluated by quantitative flow cytometry assays. Finally, we combined the enhancer::reporter assays with candidate TF overexpression to evaluate the relationship between the TFs, the enhancers, and early vertebrate retinal development. Statistical tests included ANOVA, Kruskal-Wallis, or unpaired t-tests. ResultsTwo regulatory elements, ECR9 and ECR65, were identified to be active in ThrbCRM1(+) restricted RPCs. Candidate bHLH binding sites were identified as critical sequences in both elements. Overexpression of candidate bHLH TFs revealed specific enhancer-bHLH interactions. Nhlh1 overexpression expanded ECR65 activity into the Vsx2(+) RPC population, and overexpression of NeuroD1/NeuroG2/NeuroD4 had a similar effect on ECR9. Furthermore, bHLHs that were able to activate ectopic ECR9 reporter were able to induce endogenous Otx2 expression. ConclusionsThis work reports a large-scale screen to identify spatiotemporally specific regulatory elements near the Onecut1 locus. These elements were used to identify distinct populations in the developing retina. In addition, fate-restricted regulatory elements responded differentially to bHLH factors, and suggest a role for retinal bHLHs upstream of the Otx2 and Onecut1 genes during the formation of restricted RPCs from multipotent RPCs.

developmental biology↗

bioRxiv2019

CHROMATIX: computing the functional landscape of many-body chromatin interactions in transcriptionally active loci

Chromatin interactions are important for gene regulation and cellular specialization. Emerging evidence suggests many-body spatial interactions can play important roles in condensing super-enhancer regions into a cohesive transcriptional apparatus. Chromosome conformation studies using Hi-C are limited to pairwise, population-averaged interactions; therefore, not suitable for direct assessment of many-body interactions. We describe a computational model, CHROMATIX, that reconstructs structural ensembles based on Hi-C data and identifies significant many-body interactions. For a diverse set of highly-active transcriptional loci with at least 2 super-enhancers, we detail the many-body functional landscape and show DNase-accessibility, POLR2A binding, and decreased H3K27me3 are predictive of interaction-enriched regions.

bioinformatics↗

bioRxiv2019

Cytokine and Growth Factor Response in a Rat Model of Radiation Induced Injury to the Submental Muscles

Submental muscles (i.e. mylohyoid and geniohyoid) play a vital role during swallowing, protecting the airway from ingested material. To design therapies to reduce the functional deficits associated with radiation treatment relies in part on our understanding of the changes in the cytokine and growth factor response that can impact muscle function. The purpose of this study is to quantify changes in the inflammatory, pro-fibrotic, and pro-angiogenic factors following 48Gy of fractionated radiation to the mylohyoid muscle. We hypothesized that (1) irradiation will provoke increases in TGF-1{beta} and MMP-2 mRNA in the mylohyoid muscle; and (2) muscles surrounding the target location (i.e. geniohyoid and digastric muscles) will exhibit similar alterations in their gene expression profiles. Rats were exposed to 6 fractions of 8Gy using a 6MeV electron beam on a clinical linear accelerator. The highest dose curve was focused at the mylohyoid muscle. After 2-and 4-weeks post-radiation, the mylohyoid, geniohyoid, and digastric muscles were harvested. Expression of TNF-, IFN{gamma}, IL-1{beta}, IL-6, TGF-1{beta}, VEGF, MMP-2, and MMP-9 mRNA was analyzed via PCR and/or RT-PCR. TGF-1{beta}, MMP-2, and IL-6 expression was upregulated in the irradiated mylohyoid compared to nonirradiated controls. No notable changes in TNF-, IFN{gamma}, and IL-1{beta} mRNA expression was observed in irradiated muscles. Differing expression profiles were found in the surrounding muscles post-radiation. Results demonstrated that irradiation provokes molecular signals involved in the regulation of the extracellular matrix, which could lead to fibrosis or atrophy in the swallowing muscle after radiation.

molecular biology↗

bioRxiv2019

Collateral fitness effects of mutations

The distribution of fitness effects (DFE) of mutation plays a central role in constraining protein evolution. The underlying mechanisms by which mutations lead to fitness effects are typically attributed to changes in protein specific activity or abundance. Here, we reveal the importance of a mutations collateral fitness effects, which we define as effects that do not derive from changes in the proteins ability to perform its physiological function. We comprehensively measured the collateral fitness effects of missense mutations in the E. coli TEM-1 {beta}-lactamase antibiotic resistance gene using growth competition experiments in the absence of antibiotic. At least 42% of missense mutations in TEM-1 were deleterious, indicating that for some proteins, collateral fitness effects occur as frequently as effects on protein activity and abundance. Deleterious mutations caused improper post-translational processing, incorrect disulfide-bond formation, protein aggregation, changes in gene expression, and pleiotropic effects on cell phenotype. Deleterious collateral fitness effects occurred more frequently in TEM-1 than deleterious effects on antibiotic resistance in environments with low concentrations of the antibiotic. The surprising prevalence of deleterious collateral fitness effects suggests they may play a role in constraining protein evolution, particularly for highly-expressed proteins, for proteins under intermittent selection for their physiological function, and for proteins whose contribution to fitness is buffered against mutations with deleterious effects on protein activity and protein abundance. Significance StatementMutations provide the source of genetic variability upon which evolution acts. Deleterious protein mutations are commonly thought of in terms of how they compromise the proteins ability to perform its physiological function. However, mutations might also be deleterious if they cause negative effects on one of the countless other cellular processes. The frequency and magnitude of such collateral fitness effects is unknown. Our systematic study of mutations in a bacterial protein finds widespread collateral fitness effects that were associated with protein aggregation, improper protein processing, incomplete protein transport across membranes, incorrect disulfide-bond formation, induction of stress-response pathways, and unexpected changes in cell properties. Our results suggest that deleterious collateral fitness effects may be an important constraint on protein evolution.

evolutionary biology↗

bioRxiv2019

New flat embedding method for transmission electron microscopy reveals an unknown mechanism of tetracycline

Transmission electron microscopy (TEM) is an important imaging technique in bacterial research and requires ultrathin sectioning of resin embedding of cell pellets. This method consumes milli- to deciliters of culture and results in sections of randomly orientated cells. For rod-shaped bacteria, this makes it exceedingly difficult to find longitudinally cut cells, which precludes large-scale quantification of morphological phenotypes. Here, we describe a new fixation method using either thin agarose layers or carbon-coated glass surfaces that enables flat embedding of bacteria. This technique allows for the observation of thousands of longitudinally cut rod-shaped cells per single section and requires only microliter culture volumes. We successfully applied this technique to Gram-positive Bacillus subtilis, Gram-negative Escherichia coli, the tuberculosis vaccine strain Mycobacterium bovis BCG, and the cell wall-lacking mycoplasma Acholeplasma laidlawii. To assess the potential of the technique to quantify morphological phenotypes, we examined cellular changes induced by a panel of different antibiotics. Surprisingly, we found that the ribosome inhibitor tetracycline causes significant deformations of the cell membrane. Further investigations showed that the presence of tetracycline in the cell membrane changes membrane organization and affects the peripheral membrane proteins MinD, MinC, and MreB, which are important for regulation of cell division and elongation. Importantly, we could show that this effect is not the result of ribosome inhibition but is a secondary antibacterial activity of tetracycline that has defied discovery for more than 50 years.\n\nSignificanceBacterial antibiotic resistance is a serious public health problem and novel antibiotics are urgently needed. Before a new antibiotic can be brought to the clinic, its antibacterial mechanism needs to be elucidated. Transmission electron microscopy is an important tool to investigate these mechanisms. We developed a flat embedding method that enables examination of many more bacterial cells than classical protocols, enabling large-scale quantification of phenotypic changes. Flat embedding can be adapted to most growth conditions and microbial species and can be employed in a wide variety of microbiological research fields. Using this technique, we show that even well-established antibiotics like tetracycline can have unknown additional antibacterial activities, demonstrating how flat embedding can contribute to finding new antibiotic mechanisms.

microbiology↗

bioRxiv2019

Genome assembly of the common pheasant Phasianus colchicus, a model for speciation and ecological genomics

The common pheasant (Phasianus colchicus) in the order Galliformes and the family Phasianidae, has 30 subspecies distributed across its native range in the Palearctic realm and has been introduced to Europe, North America, and Australia. It is an important game bird often subjected to wildlife management as well as a model species to study speciation, biogeography and local adaptation. However, the genomic resources for the common pheasant are generally lacking. We sequenced a male individual of the subspecies torquatus of the common pheasant with the Illumina Hiseq platform. We obtained 94.88 Gb of usable sequences by filtering out low-quality reads of the raw data generated. This resulted in a 1.02 Gb final assembly, which equals the estimated genome size. BUSCO analysis using chicken as a model showed that 93.3% of genes were complete. The contig N50 and scaffold N50 sizes were 178 kb and 10.2 Mb, respectively. All these indicate that we obtained a high-quality genome assembly. We annotated 16,485 protein-coding genes and 123.3 Mb (12.05 % of the genome) of repetitive sequences by ab initio and homology-based prediction. Furthermore, we applied a RAD-sequencing approach for another 45 individuals of seven representative subspecies in China and identified 4,376,351 novel single nucleotide polymorphism (SNPs) markers. Using this unprecedented dataset, we uncover the geographic population structure and genetic introgression among common pheasants in China. Our results provide the first high-quality reference genome for the common pheasant and a valuable genome-wide SNP database for studying population genomics and demographic history.

genomics↗