title: Metabolic switch in the aging astrocyte evidenced via integrative approach comprising network and transcriptome analyses

abstract:
Central energy metabolism is a pivotal process dysregulated during brain aging. The neuron and the astrocyte form an extensive interconnected metabolic network that allows achieving the high energy demand required by the neuron to propagate information in the brain. While most of this energy is utilized to re-establish cation gradients in neurons and glial cells, which specific genes in the neuron-astrocyte metabolic network are essential for continuous neurotransmission and are responsible for cognitive decline during brain aging remains largely unknown.

To identify these gene products, we used a novel approach to analyze the neuron-astrocyte metabolic network, integrating network flux (optimality) and structure (centrality) and determined how the contribution of each gene in the network affected its function. Genes with the highest optimality and centrality scores were termed "hub genes." They were searched in astrocyte and neuron transcriptomic databases to identify "differential hub genes," which were differentially expressed during neurotransmission or aging.

The identified differential hub genes suggest that during brain aging: 1) The neuron suffers energetic deficit by substantial downregulation of Krebs cycle genes including mdh1 and mdh2 (malate-aspartate shuttle), while the astrocyte undergoes a metabolic switch from aerobic glycolysis to oxidative phosphorylation, hampering the supply of lactate to the neuron; 2) Branched-chain amino acid (BCAA) degradation hub genes were downregulated, including hub gene dld, an integrative gene that encodes for a subunit in BCAA-, pyruvate- and - ketoglutarate dehydrogenase complexes; and 3) Increased ketone body synthesis in the neuron and augmented astrocytic utilization, in line with neuronal energy deficit in favor of astrocytes.

Differential hub gene identification was robust and resulted in novel candidates for future pre-clinical studies targeting energy metabolism to prevent age-associated cognitive decline. Importantly, our approach narrows down the number of candidate genes identified in transcriptomic databases by two orders of magnitude. This method may be applied to other metabolic cellular models in future omics studies.


title: Autism in a dish: ES cell models of autism with copy number variations reveal cell-type-specific vulnerability

abstract: Human genetics has identified numerous single nucleotide variations (SNVs) and copy number variations (CNVs) associated with autism spectrum disorders (ASD) and other psychiatric disorders. However, the lack of standardized biological resources impedes understanding of the common pathophysiology of ASD. Here, using next-generation chromosome engineering based on the CRISPR/Cas9 system, we established a biological resource including 65 genetically modified mouse embryonic stem cell (mESC) lines as genetic models of human SNVs and CNVs. To illustrate cell-type and CNV specific molecular features of ASD, we performed single-cell RNA sequencing (37,397 cells in total), morphological, and physiological analyses using 12 representative cell lines with CNVs highly associated with ASD. These results uncover gene ontology (GO) terms, canonical pathways, upstream regulators, and related neuropsychiatric disorders in a cell-type and CNV specific manner.

category: neuroscience


title: Human neural progenitors establish a diffusion barrier in the ER membrane during cell division

abstract:
Asymmetric segregation of cellular components regulates the fate and behavior of somatic stem cells. Similar to dividing budding yeast and precursor cells in C. elegans, it has been shown that mouse neural progenitors establish a diffusion barrier in the membrane of the endoplasmic reticulum (ER), which has been associated with asymmetric partitioning of damaged proteins and cellular age. However, the existence of an ER-diffusion barrier in human cells remains unknown. Here we used fluorescence loss in photobleaching (FLIP) imaging to show that human embryonic stem cell (hESC)- and induced pluripotent stem cell (iPSC)-derived neural progenitor cells establish an ER-diffusion barrier during cell division. The human ER-diffusion barrier is regulated via Lamin-dependent mechanisms and is associated with asymmetric segregation of mono- and polyubiquitinated, damaged proteins. Further, forebrain regionalized organoids derived from hESCs were used to show the establishment of an ER-membrane diffusion barrier in more naturalistic tissues mimicking early steps of human brain development. Thus, the data provided here show that human neural progenitors establish a diffusion barrier during cell division in the membrane of the ER, which may allow for asymmetric segregation of cellular components, contributing to the fate and behavior of human neural progenitor cells.

SummaryHuman neural progenitors (NPCs) establish a diffusion barrier during cell division in the membrane of the endoplasmic reticulum, allowing for asymmetric segregation of cellular components, which may contribute to the fate and behavior of human NPCs.


title: Micapipe: a pipeline for multimodal neuroimaging and connectome analysis

abstract: AO_SCPLOWBSTRACTC_SCPLOWMultimodal magnetic resonance imaging (MRI) has accelerated human neuroscience by fostering the analysis of brain structure, function, and connectivity across multiple scales and in living brains. The richness and complexity of multimodal neuroimaging, however, demands processing methods to integrate information across modalities and different spatial scales. Here, we present micapipe, an open processing pipeline for BIDS-conform multimodal MRI datasets. micapipe can generate i) structural connectomes derived from diffusion tractography, ii) functional connectomes derived from resting-state signal correlations, iii) geodesic distance matrices that quantify cortico-cortical proximity, and iv) microstructural profile covariance matrices that assess inter-regional similarity in cortical myelin proxies. These matrices are routinely generated across established 18 cortical parcellations (100-1000 parcels), in addition to subcortical and cerebellar parcellations. Results are represented on three different surface spaces (native, conte69, fsaverage5), and outputs are BIDS-conform. Processed outputs can be quality controlled at the individual and group level. micapipe was tested on several datasets and is available at https://github.com/MICA-MNI/micapipe, documented at https://micapipe.readthedocs.io/, and containerized as a BIDS App http://bids-apps.neuroimaging.io/apps/. We hope that micapipe will foster robust and integrative studies of human brain microstructure, morphology, and connectivity.


title: Stress-Mediated Attenuation of Translation Undermines T Cell Tumor Control

abstract: Protein synthesis enables cell growth and survival, but the molecular mechanisms through which T cells suppress or maintain protein translation in the stress of solid tumors are unknown. Using mouse models and human tumors we demonstrate that protein translation in T cells is repressed by the solid tumor microenvironment (TME) due to activation of the unfolded protein response (UPR) via phosphorylation of the  subunit of eukaryotic translation initiation factor 2 (p-eIF2). Given that acute glucose deprivation in T cells exacerbated p-eIF2, we show that metabolic reprogramming toward glycolytic independence allays the UPR and p-eIF2, enabling sustained protein translation in T cells in TME stress. UPR mitigation was associated with enhanced degradation of proteins in antitumor T cells, as proteasome inhibition resulted in eIF2 phosphorylation, attenuation of translation, and loss of antitumor efficacy. In contrast, proteasome stimulation relieved translation inhibition, inducing robust T cell tumor control, offering a new therapeutic avenue to fuel the efficacy of tumor immunotherapy.

category: immunology


title: Fezf2 and Aire1 evolutionary trade-off in negative selection of T cells in the thymus

abstract: In vertebrates, thymus expression of various body proteins to eliminate autoreactive T cells during the negative selection process is orchestrated by AIRE and FEZF2. T cells first appeared in vertebrates. However, the evolutionary history of these two genes in relation to T cells emergence is still not clear. Specifically, it is still not known, whether these two genes emerged concurrently to support the negative selection process. Furthermore, whether there is an evolutionary trade-off between these two genes is not known. Whether these two genes play a similar role in controlling auto-reactivity elimination in lampreys and invertebrates is also unknown. We used a plethora of phylogenetic analysis tools including; multiple sequence alignment, phylogenetic tree building, ancestral sequence reconstruction, functional specificity investigation, and positive selection analysis to address these questions. We found that these two genes represent two distinct pathways of negative selection with two unique origins. While AIRE emerged during the divergence of T cells in vertebrates, FEZF2 is far ancient with homologs in invertebrates including Cnidaria, Trichoplax. We found that FEZF2 structure is highly conserved between invertebrates and vertebrates. Moreover, the genes controlled by both families included a mixture of ancient and recently diverged genes. However, we found that AIRE contains an LXXLL motif for binding nuclear receptors. Conversely, FEZF2 possesses several motifs known to play a role in autophagy, such as DKFPHP, SYSELWKSSL, and SYSEL. However, both genes contain similar motifs such as MAPK regulating motifs. Interestingly, AIRE seems to be lacking in lampreys, in contrast to FEZF2. Taken together, our investigation hints that FEZF2 was initially employed to control a rudimentary auto-reactivity elimination process in invertebrates, then evolved to play a part in controlling a negative selection process in early vertebrates and higher vertebrates. The emergence of AIRE seems to be correlated with controlling the negative selection process in higher vertebrates. The results demonstrate a strong evolutionary trading-off process, where FEZF2 kept controlling certain biological processes whereas AIRE gained control of others. Several critical genes are controlled by both genes, to ensure an adequate negative selection process.

category: evolutionary biology


title: Deep Mendelian Randomization: Investigating the causal knowledge of genomic deep learning models

abstract: Multi-task deep learning (DL) models can accurately predict diverse genomic marks from sequence, but whether these models learn the causal relationships between genomic marks is unknown. Here, we describe Deep Mendelian Randomization (DeepMR), a method for estimating causal relationships between genomic marks learned by genomic DL models. By combining Mendelian Randomization with in silico mutagenesis, DeepMR obtains local (locus specific) and global estimates of (an assumed) linear causal relationship between marks. In a simulation designed to test recovery of pairwise causal relations between transcription factors (TFs), DeepMR gives accurate and unbiased estimates of the  true global causal effect, but its coverage decays in the presence of sequence-dependent confounding. We then apply DeepMR to examine the global relationships learned by a state-of-the-art DL model, BPNet [Avsec et al., 2020], between TFs involved in reprogramming. DeepMRs causal effect estimates validate previously hypothesized relationships between TFs and suggest new relationships for future investigation.

category: genomics


title: Rapid Carbon Dioxide Capture and Short-Term Biocompatible Sequestration in Aquatic Environments by Monoethanolamine Scrubbing within Calcium Alginate Gel

abstract: Alginate is a biopolymer extracted from the cell walls of algae, and can crosslink with divalent cations to form an insoluble hydrogel. In this paper, we develop a method to immobilize monoethanolamine, an amine CO2 scrubber, within calcium alginate gel. By mixing monoethanolamine into an alginate solution as the gel was formed, we suspended the compound in the gel, facilitating a means to capture carbon dioxide directly from aquatic environments into the gel, while tethering monoethanolamine and the products formed from CO2 capture to the gel. To delay the eventual diffusion of monoethanolamine out of the gel, we investigated (1) the effect of increasing alginate concentration and (2) the effect of additional alginate layers on the outward diffusion of dye placed in the center of the bead. Using ultraviolet-visible spectroscopy to quantify diffusion rates over time, we determined that increased alginate concentration paired with increased layering significantly decreased the rate of outward diffusion. Finally, we prepared beads using North Atlantic seawater as a solvent and compared the rate of dye leakage in seawater and distilled water to that in beads prepared in distilled water. Expectedly, we concluded that beads prepared with solvents isotonic to their environments would exhibit less leakage as well as greater mechanical stability, resisting swelling, bursting, or splitting behaviors.

category: bioengineering


title: 3D printed bioreactor enabling the physiological culture and the study of pathological processes in large vessels.

abstract:
Routine cardiovascular interventions such as balloon angioplasty, result in vascular activation and remodeling, often requiring re-intervention. 2D in vitro culture models and small animal experiments have enabled the discovery of important molecular and cellular pathways involved in this process, however the clinical translation of these results is often underwhelming. There is a critical need for an ex vivo model representative of the human vascular physiology and encompassing the complexity of the vascular wall and the physical forces regulating its function. Vascular bioreactors for ex vivo culture of large vessels are viable alternatives, but their custom-made design and insufficient characterization often hinders the reproducibility of the experiments.

The objective of the study was to design and validate a novel 3D printed cost-efficient and versatile perfusion system, capable of sustaining the viability and functionality of large porcine arteries for 7 days and enabling monitoring of post-injury remodeling.

MultiJet Fusion 3D printing technology was used to engineer the  EasyFlow insert, converting a conventional 50 ml centrifuge tube into a mini bioreactor. Porcine carotid arteries either left untreated or injured with a conventional angioplasty balloon, were cultured under pulsatile flow for up to 7 days. Pressure, heart rate, medium viscosity and shear conditions were adjusted to represent the typical arterial physiology. Tissue viability, cell activation and matrix remodeling were analyzed by immunohistochemistry, and vascular function was monitored by duplex ultrasound.

Physiological blood flow conditions in the EasyFlow bioreactor preserved endothelial coverage and smooth muscle organization and extracellular matrix structure in the vessel wall, as compared to static culture. Injured arteries presented hallmarks of early remodeling, such as intimal denudation, smooth muscle cell disarray and media/adventitia activation in flow culture. Duplex ultrasound confirmed physiological hemodynamic conditions, dose-dependent vasodilator response to nitroglycerin in untreated vessels and impaired dilator response in angioplastied vessels. We here validate a low-cost, robust and reproducible system to study vascular physiopathology, laying the basis for future investigations into the pathological remodeling of blood vessels and creating a platform to test novel therapies and devices ex vivo, in a patient relevant system.


title: Generative pretraining from large-scale transcriptomes: Implications for single-cell deciphering and clinical translation

abstract: Exponential accumulation of single-cell transcriptomes poses great challenge for efficient assimilation. Here, we present an approach entitled tGPT towards integration of 22.3 million single-cell transcriptomes by modeling gene expression rankings as generative pretraining task. tGPT is conceptually simple in that it autoregressively models the ranking of a gene in the context of its preceding neighbors. We demonstrated the high performance of tGPT on a range of fundamental single-cell analysis tasks and novel applications on bulk tissues. The single-cell clusters and cell lineage trajectories derived from tGPT are highly aligned with known cell labels and states. The feature patterns of tumor bulk tissues learned by tGPT are associated with a wide range of genomic alteration events, prognosis and treatment outcome of immunotherapy. tGPT represents a new analytical paradigm for integrating and deciphering massive amount of transcriptome data and it will facilitate the interpretation and clinical translation of single-cell transcriptomes.

category: bioinformatics


title: ImmunoTyper-SR: A Novel Computational Approach for Genotyping Immunoglobulin Heavy Chain Variable Genes using Short Read Data

abstract: Human immunoglobulin heavy chain (IGH) locus on chromosome 14 includes more than 40 functional copies of the variable gene (IGHV), which, together with the joining genes (IGHJ), diversity genes (IGHD), constant genes (IGHC) and immunoglobulin light chains, code for antibodies that identify and neutralize pathogenic invaders as a part of the adaptive immune system. Because of its highly repetitive sequence composition, the IGH locus has been particularly difficult to assemble or genotype through the use of standard short read sequencing technologies. Here we introduce ImmunoTyper-SR, an algorithmic method for genotype and CNV analysis of the germline IGHV genes using Illumina whole genome sequencing (WGS) data. ImmunoTyper-SR is based on a novel combinatorial optimization formulation that aims to minimize the total edit distance between reads and their assigned IGHV alleles from a given database, with constraints on the number and distribution of reads across each called allele. We have validated ImmunoTyper-SR on 12 individuals with Illumina WGS data from the 1000 Genomes Project, whose IGHV allele composition have been studied extensively through the use of long read and targeted sequencing platforms, as well as nine individuals from the NIAID COVID Consortium who have been subjected to WGS twice. We have then applied ImmunoTyper-SR on 585 samples from the NIAID COVID Consortium to investigate associations between distinct IGHV alleles and anti-type I IFN autoantibodies which have been linked to COVID-19 severity.


title: SleepMat: A New Behavioral Analysis Software Program for Sleep and Circadian Rhythms

abstract: Drosophila is a premier model for the study of circadian rhythms and sleep, revealing molecular mechanisms that are conserved with vertebrates, including humans. The Drosophila Activity Monitoring (DAM) system has been employed for automated, high throughput analyses, enabling measures of a wide range of measures of circadian and sleep, including period, rhythmicity, anticipation, sleep amount, bout length, and bout number. Yet there are no publicly available programs that capture the full breadth of these measures. Here we develop a new program SleepMat that analyzes a uniquely broader range of circadian and sleep parameters. The program is built on a Matlab platform, employs an easy-to-use graphic user interface, and is highly flexible to customize data inputs. This program will enable a user-friendly high throughput analysis of a broad range of sleep and circadian parameters that can be coupled to the power of Drosophila genetics.


title: Syllable-PBWT for space-efficient haplotype long-match query

abstract: The positional Burrows-Wheeler transform (PBWT) has led to tremendous strides in haplotype matching on biobank-scale data. For genetic genealogical search, PBWT-based methods have optimized the asymptotic runtime of finding long matches between a query haplotype and a predefined panel of haplotypes. However, to enable fast query searches, the full-sized panel and PBWT data structures must be kept in memory, preventing existing algorithms from scaling up to modern biobank panels consisting of millions of haplotypes. In this work, we propose a space-efficient variation of PBWT named Syllable-PBWT, which divides every haplotype into syllables, builds the PBWT positional prefix arrays on the compressed syllabic panel, and leverages the polynomial rolling hash function for positional substring comparison. With the Syllable-PBWT data structures, we then present a long match query algorithm named Syllable-Query. Compared to Algorithm 3 of Sanaullah et al. (2021), the most time- and space-efficient previously published solution to the long match query problem, Syllable-Query reduced the memory use by a factor of over 100 on both the UK Biobank genotype data and the 1000 Genomes Project sequence data. Surprisingly, the smaller size of our syllabic data structures allows for more efficient iteration and CPU cache usage, granting Syllable-Query even faster runtime than existing solutions. The implementation of our algorithm is available at https://github.com/ZhiGroup/Syllable-PBWT.


title: Clinical Time-to-Event Prediction Enhanced by Incorporating Compatible Related Outcomes

abstract: Accurate time-to-event (TTE) prediction of clinical outcomes from personal biomedical data is essential for precision medicine. It has become increasingly common that clinical datasets contain information for multiple related patient outcomes from comorbid diseases or multifaceted endpoints of a single disease. Various TTE models have been developed to handle competing risks that are related to mutually exclusive events. However, clinical outcomes are often non-competing and can occur at the same time or sequentially. Here we develop TTE prediction models with the capacity of incorporating data of compatible related clinical outcomes. We test our method on real and synthetic data and find that the incorporation of related auxiliary clinical outcomes can: 1) significantly improve the TTE prediction performance of convention Cox model while maintaining its interpretability; 2) further improve the performance of the state-of-the-art deep learning based models. While the auxiliary outcomes are utilized for model training, the model deployment is not limited by the availability of the auxiliary outcome data because the auxiliary outcome information is not required for the prediction of the primary outcome once the model is trained.


title: Metabolic predictors of phenotypic traits can replace and complement measured clinical variables in transcriptome-wide association studies

abstract:
Transcriptome-wide association studies (TWAS) can provide valuable insights into biological and disease-underlying mechanisms. For studying clinical effects, availability of (confounding) phenotypic traits is essential. The (re)use of RNA-seq or other omics data can be limited by missing, incomplete, or inaccurate phenotypic information. A possible solution are molecular predictors inferring clinical or behavioral phenotypic traits. Such predictors have been developed based on different omics data types and are being applied in various studies.

In this study, we applied 17 metabolic predictors to infer various traits, including diabetes status or exposure to lipid medication. We evaluated whether these metabolic surrogates can be used as an alternative to reported information for studying the respective phenotypes using TWAS. Our results revealed that in most cases, the use of metabolic surrogates yields similar results compared to using reported information, making them suitable substitutes for such studies.

The application of metabolomics-derived surrogate outcomes opens new possibilities for reuse of multi-omics data sets, especially in situations where availability of clinical metadata is limited. Missing or incomplete information can be complemented by these surrogates, thereby increasing the size of available data sets. Studies would likely also benefit from the use of such surrogates to correct for potential biological confounding. This should be further investigated.

Author summaryTranscriptome-wide association studies (TWAS) can be used to associate gene expression levels with phenotypic traits. These associations can provide insights into biological mechanisms including those that underlie diseases. Such studies require molecular profiling data from a large number of individuals as well as information on the phenotypic trait of interest. Biobanks that collect samples and corresponding molecular data, also collect information on phenotypic traits or clinical information. However, this information can be heterogeneous and/or incomplete, or a certain piece of information could be missing entirely. In this study, we apply metabolic predictors to infer various traits, including diabetes status or exposure to lipid medication. We evaluate whether these metabolic surrogates can be used as an alternative to reported information for studying the respective phenotypes using TWAS. Our results reveal that in many cases, the use of metabolic surrogates yields similar results compared to using reported information, making them suitable substitutes for such studies. The possibility of using these surrogate outcomes can thus increase the size of data sets for studies where phenotypic information is incomplete or missing.


title: mSigHdp: hierarchical Dirichlet process mixture modeling for mutational signature discovery

abstract:
Mutational signatures are characteristic patterns of mutations caused by endogenous or exogenous mutational processes. These signatures can be discovered by analyzing mutations in a large set of samples - usually somatic mutations in tumor samples. Most approaches to mutational-signature discovery are based on non-negative matrix factorization. Alternatively, signatures can be inferred using hierarchical Dirichlet process (HDP) mixture models, an approach that has been relatively little explored. These models assign mutations to clusters and view each cluster of mutations as being generated from a particular mutational process. Here we describe mSigHdp, an improved approach to using HDP mixture models to discover mutational signatures. We benchmarked mSigHdp and several other programs on realistic synthetic data. For single-base mutations, mSigHdp and the widely used SigProfilerExtractor discovered signatures better than the other 2 programs and had different strengths: mSigHdp discovered more of the signatures present in the synthetic data, while SigProExtractor discovered fewer false positives. mSigHdp was better able to discover rare signatures, which may be an advantage, since most common signatures have probably already been discovered. For small insertion-and-deletion mutations, mSigHdp discovered signatures better than the other 3 programs. Thus, mSigHdp is an advance for discovering rare SBSs mutational signatures and for discovering small insertion-and-deletion mutational signatures.

AvailabilitymSigHdp is available at GitHub public repositories https://github.com/steverozen/mSigHdp and https://github.com/steverozen/hdpx. Synthetic data, code for generating the synthetic data, code for running the mutational-signature discovery programs and analyzing their results, the main outputs of the programs, and code for generating the data figures in this paper are available at https://github.com/Rozen-Lab/Liu_et_al_Sup_Files.

Supplementary informationSupplementary information is provided on the bioRxiv web site for this manuscript.


title: ReadBouncer: Precise and Scalable Adaptive Sampling for Nanopore Sequencing

abstract:
Nanopore sequencers allow targeted sequencing of interesting nucleotide sequences by rejecting other sequences from individual pores. This feature facilitates the enrichment of low-abundant sequences by depleting overrepresented ones in-silico. Existing tools for adaptive sampling either apply signal alignment, which cannot handle human-sized reference sequences, or apply read mapping in sequence space relying on fast GPU base callers for real-time read rejection. Using nanopore long-read mapping tools is also not optimal when mapping shorter reads as usually analyzed in adaptive sampling applications. Here we present a new approach for nanopore adaptive sampling that combines fast CPU and GPU base calling with read classification based on Interleaved Bloom Filters (IBF). Read-Bouncer improves the potential enrichment of low abundance sequences by its high read classification sensitivity and specificity, outperforming existing tools in the field. It robustly removes even reads belonging to large reference sequences while running on commodity hardware without graphical processing units (GPUs), making adaptive sampling accessible for in-field researchers. Readbouncer also provides a user-friendly interface and installer files for end-users without a bioinformatics background.

AvailabilityThe C++ source code of ReadBouncer is available at (https://gitlab.com/dacs-hpi/readbouncer).


title: Electrocardiogram feature extraction and interval measurements using optimal representative cycles from persistent homology

abstract:
Cardiovascular diseases are among the leading causes of death, and their early detection and treatment is important for lowering their prevalence and mortality rate. Electrocardiograms (ECGs) record electrical activity of the heart to provide information used to diagnose and treat various cardiovascular diseases. Many approaches to computer-aided ECG analysis have been performed, including Fourier analysis, principal component analysis, analyzing morphological changes, and machine learning. Due to the high accuracy required of ECG-analysis software, there is no universally-agreed upon algorithm to identify P,Q,R,S, and T-waves and measure intervals of interest. Topological data analysis uses tools from algebraic topology to quantify hole-like shapes within data, and methods using persistence statistics and fractal dimension with machine learning have been applied to ECG signals in the context of detecting arrhythmias within recent years. To our knowledge, there does not exist a method of identifying P,Q,S, and T-waves and measuring intervals of interest which relies on topological features of the data, and we propose a novel topological method for performing these aspects of ECG analysis. Specifically, we establish criteria to identify cardinality-minimal and area-minimal 1-cycles with certain properties as P,Q,S, and T-waves. This yields a procedure for measuring the PR-interval, QT-interval, ST-segment, QRS-duration, P-wave duration, and T-wave duration in Lead II ECG data. We apply our procedure to 400 sets of simulated Lead II ECG signals and compare with the interval values set by the model. Additionally, the algorithm is used to identify cardinality-minimal and area-minimal 1-cycles as P,Q,S, and T-waves in two sets of 200 randomly sampled Lead II ECG signals of real patients with 11 common rhythms. Analysis of optimal 1-cycles identified as P,Q,S, and T-waves and comparison of interval measurements shows that 1-cycle reconstructions can provide useful information about the ECG signal and could hold utility in characterizing arrhythmias.

Author summaryTopological data analysis (TDA) has been a rapidly growing field within the past 15 years and has found applications across many fields. In the context of TDA, several algorithms primarily using persistence barcode statistics and machine learning have been applied to electrocardiogram (ECG) signals in recent years. We use a topological data-analytic method to identify subsets of an ECG signal which are representative of certain topological features in the ECG signal, and we propose that those subsets coincide with the P,Q,S, and T-waves in the ECG signal. We then use information about these subsets of the signal identified as P,Q,S, and T-waves to measure the PR-interval, QT-interval, ST-segment, QRS-duration, P-wave duration, and T-wave duration. We demonstrate our method on both simulated and real Lead II ECG data. These results show how identifying subsets of an ECG signal with certain topological properties could be used in analyzing the morphology of the signal over time and in arrhythmia-detection algorithms.


title: Toward an atomistic model of SARS-CoV-2

abstract: The causative pathogen of Coronavirus disease 2019 (COVID-19), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is an enveloped virus assembled by a lipid envelope, a positive-sense single-stranded RNA, and four structural proteins: the spike (S), membrane (M), envelope (E), and nucleocapsid (N) proteins. Extensive experimental and computational studies have been carried out to reveal the architecture of the virus, but an intact and high-resolution structure of the virus is still desired. In this work, we construct atomistic models of the intact SARS-CoV-2 (without complete RNA) by fully employing the latest cryo-ET data, in combination with the available experimentally resolved protein structures, structure prediction and modeling methods, as well as coarse-grained molecular dynamics (MD) simulations. The atomistic model will not only provide a 3D structure for scientific demonstration and education, but also offer a framework for future exascale all-atom MD simulations to understand the dynamics of the intact virus and its mutations.

category: biophysics


title: Proteomics and Functional Analysis Revealed TaGSTU6/TaCBSX3 Enhances Wheat Resistance to Powdery Mildew

abstract:
Wheat stripe rust and powdery mildew are important worldwide diseases of wheat (Triticum aestivum). The wheat cultivar Xingmin318 (XM318) is resistant to both wheat stripe rust and powdery mildew, which are caused by Puccinia striiformis f. sp. tritici (Pst) and Blumeria graminis f. sp. tritici (Bgt), respectively. To explore the molecular mechanisms of wheat defenses against Pst and Bgt, quantitative proteomic analyses of XM318 inoculated with Pst and Bgt, respectively, were performed using tandem mass tags (TMT) technology. A total of 741 proteins were identified as differentially accumulated proteins (DAPs). Bioinformatics analyses indicated that some functional categories, including antioxidant activity, exhibited obvious differences between Pst and Bgt infections. Intriguingly, only 42 DAPs responded to both Pst and Bgt infections. Twelve DAPs were randomly selected for RT-qPCR analysis, and the mRNA expression levels of eleven were consistent with their protein expression. Furthermore, gene silencing using the virus-induced gene silencing system indicated that glutathione S-transferase (TaGSTU6) has an important role in resistance to Bgt but not to Pst. TaGSTU6 was shown to interact with the cystathionine beta-synthase (CBS) domain-containing protein (TaCBSX3). Knockdown of TaCBSX3 expression only reduced wheat resistance to Bgt infection. Overexpression of TaGSTU6 and TaCBSX3 in Arabidopsis (Arabidopsis thaliana) promoted plant resistance to Pseudomonas syringae pv. tomato DC3000 (Pst DC3000). Our results indicated that the TaGSTU6 interacting with TaCBSX3 only confers wheat resistance to Bgt, suggesting that wheat has different response mechanisms to Pst and Bgt stress.

One-sentence summaryProteomics revealed a difference in the wheat resistance response to Pst and Bgt, and the TaGSTU6/TaCBSX3 interaction plays an important role only in wheat resistance to Bgt.

category: pathology


title: Capturing early human memory consolidation utilizing the higher functional specificity of 7T compared to 3T-fMRI

abstract: Functional magnetic resonance imaging (fMRI) visualizes brain structures at increasingly higher resolution and better signal-to-noise ratio (SNR) as field strength increases. Yet, mapping the BOLD response to distinct neuronal processes continues to be challenging. Here, we performed 3T and 7T-fMRI analysis of motor-task activation and resting-state connectivity with adjusted SNR. We then applied graph theory to analyze resting-state neuronal networks detected by fMRI after a simple motor task. Despite adjusted SNR, 7T achieved a higher functional specificity of the BOLD response than 3T-fMRI. Following the motor task, 7T-fMRI therefore enabled the detection of an  offline replay that was directly linked to brain regions associated with memory consolidation. These findings reveal how memory processing is initiated even after simple motor tasks and begins earlier than previously shown. Thus, the superior capability of 7T-fMRI to detect subtle functional dynamics promises to improve diagnostics and therapeutic assessment of neurological diseases.


title: Neural network of superiority illusion predicts the level of dopamine in striatum

abstract:
In evaluating the personality attributes and performance of the self, people are inclined to view themselves superior to others, a phenomenon known as superiority illusion (SI). This illusive outlook pervades peoples thoughts, creating hope for the future and promoting mental health. Although a specific cortico-striatal functional connectivity (FC) under dopaminergic modulation was previously shown to be implicated in SI, the underlying whole-brain mechanisms have remained unclarified. Herein, to reveal the neural network subserving individuals SI, we conducted a data-driven, machine-learning investigation to explore the resting-state FC network across the whole brain. Using the locally-acquired resting-state functional magnetic resonance imaging data (n = 123), we identified a set of 15 FCs most informative in classifying individuals with higher-versus lower-than-average levels of SI in evaluating positive trait words (area under the curve [AUC] = 0.81). Among the 15 FCs, the contribution level to the classification was 11% by the previously-highlighted cortico-striatal FC alone, but 60% by the encompassing cortico-limbico-striatal network cluster. A newly-identified, cortico-thalamic FC and another FC cluster also demonstrated substantial contribution. The classification accuracy was generalized into an independent cohort (n = 36; AUC = 0.73). Importantly, using the same set of 15 FCs, we achieved prediction on an individuals level of striatal dopamine D2 receptor availability (Pearson correlation, r = 0.46, P = 0.005). This is the first successful identification of the whole-brain neural network that simultaneously predicts the behavioral manifestation and molecular underpinning of an essential psychological process that promotes well-being and mental health.

Significance StatementSuperiority illusion (SI) is a basic self-referential framework that pervades peoples thoughts and promotes well-being and mental health. An aberrant form of SI has been reported in psychiatric conditions such as depression. Our hypothesis-free, data-driven investigation revealed the spatially-distributed neural network that for the first time achieved prediction on an individuals levels of SI and the striatal dopaminergic transmission simultaneously. In principle, this multiple-biological-layer framework can be applicable to any behavioral trait to establish a link with its underlying neural network and neurochemical properties, which could quantitatively present the relation of its aberrant form with the pathophysiology of neuropsychiatric disorders. Future clinical research may aid in deriving a diagnostic biomarker for examining the related behavioral and neurochemical characteristics within individuals.


title: Nanoparticle-delivered TLR4 and RIG-I agonists enhance immune response to SARS-CoV-2 subunit vaccine

abstract:
Despite recent success in vaccinating populations against SARS-CoV-2, concerns about immunity duration, continued efficacy against emerging variants, protection from infection and transmission, and worldwide vaccine availability, remain. Although mRNA, pDNA, and viral-vector based vaccines are being administered, no protein subunit-based SARS-CoV-2 vaccine is approved. Molecular adjuvants targeting pathogen-recognition receptors (PRRs) on antigen-presenting cells (APCs) could improve and broaden the efficacy and durability of vaccine responses. Native SARS-CoV-2 infection stimulate various PRRs, including toll-like receptors (TLRs) and retinoic-acid-inducible gene I-like receptors (RIG-I). We hypothesized that targeting the same PRRs using adjuvants on nanoparticles along with a stabilized spike (S) protein antigen could provide broad and efficient immune responses. Formulations targeting TLR4 (MPLA), TLR7/8 (R848), TLR9 (CpG), and RIG-I (PUUC) delivered on degradable polymer-nanoparticles (NPs) were combined with the S1 subunit of S protein and assessed in vitro with isogeneic mixed lymphocyte reactions (iso-MLRs). For in vivo studies, the adjuvanted nanoparticles were combined with stabilized S protein and assessed using intranasal and intramuscular prime-boost vaccination models in mice. Combination NP-adjuvants targeting both TLR and RIG-I (MPLA+PUUC, CpG+PUUC, or R848+PUUC) differentially increased proinflammatory cytokine secretion (IL-1{beta}, IL-12p70, IL-27, IFN-{beta}) by APCs cultured in vitro, and induced differential T cell proliferation. When delivered intranasally, MPLA+PUUC NPs enhanced local CD4+CD44+ activated memory T cell responses while MPLA NPs increased anti-S-protein-specific IgG and IgA in the lung. Following intramuscular delivery, PUUC-carrying NPs induced strong humoral immune responses, characterized by increases in anti-S-protein IgG and neutralizing antibody titers and germinal center B cell populations (GL7+ and BCL6+ B cells). MPLA+PUUC NPs further boosted S-protein-neutralizing antibody titers and T follicular helper cell populations in draining lymph nodes. These results suggest that SARS-CoV-2-mimicking adjuvants and subunit vaccines could lead to robust and unique route-specific adaptive immune responses and may provide additional tools against the pandemic.

GRAPHICAL ABSTRACT

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title: Detection and Interspecies Comparison of SARS-CoV-2 Delta Variant (AY.3) in Feces from a Domestic Cat and Human Samples

abstract: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections have spilled over from humans to companion and wild animals since the inception of the global COVID-19 pandemic. However, whole genome sequencing data of the viral genomes that infect non-human animal species has been scant. Here, we detected and sequenced a SARS-CoV-2 delta variant (AY.3) in fecal samples from an 11-year-old domestic house cat previously exposed to an owner who tested positive for SARS-CoV-2. Molecular testing of two fecal samples collected 7 days apart yielded relatively high levels of viral RNA. Sequencing of the feline-derived viral genomes showed the two to be identical, and differing by between 4 and 14 single nucleotide polymorphisms in pairwise comparisons to human-derived lineage AY.3 sequences collected in the same geographic area and time period. However, several mutations unique to the feline samples reveal their divergence from this cohort on phylogenetic analysis. These results demonstrate continued spillover infections of emerging SARS-CoV-2 variants that threaten human and animal health, as well as highlight the importance of collecting fecal samples when testing for SARS-CoV-2 in animals. To the authors knowledge, this is the first published case of a SARS-CoV-2 delta variant in a domestic cat in the United States.

category: microbiology


title: Aucubin promoted neuron functional recovery by suppressing inflammation and neuronal apoptosis in a spinal cord injury model

abstract: Spinal cord injury (SCI) can cause severe motor impairment. Post-SCI treatment has focused primarily on secondary injury, with neuroinflammation and neuronal apoptosis as the primary therapeutic targets. Aucubin (Au), a Chinese herbal medicine, exerts anti-inflammatory and neuroprotective effects. The therapeutic effects of Au in SCI have not been reported. We showed that Au can promote functional recovery after SCI. Recovery may occur through the toll-like receptor 4 (TLR4)/nuclear factor kappa B (NF-{kappa}B) pathway to promote M2/M1 polarization in microglia and inhibit mitochondrial dysfunction to reduce neuronal apoptosis. These biochemical changes result in reduced secondary injury and facilitate axon regeneration. Therefore, Au may be a promising post-SCI therapeutic medication.

category: cell biology


title: Rare and population-specific functional variation across pig lines

abstract:
BackgroundIt is expected that functional, mainly missense and loss-of-function (LOF), and regulatory variants are responsible for phenotypic differences among breeds, genetic lines, and varieties of livestock and crop species that have undergone diverse selection histories. However, there is still limited knowledge about the existing missense and LOF variation in livestock commercial populations, in particular regarding population-specific variation and how it can affect applications such as across-breed genomic prediction.

MethodsWe re-sequenced the whole genome of 7,848 individuals from nine commercial pig breeding lines (average sequencing coverage: 4.1x) and imputed whole-genome genotypes for 440,610 pedigree-related individuals. The called variants were categorized according to predicted functional annotation (from LOF to intergenic) and prevalence level (number of lines in which the variant segregated; from private to widespread). Variants in each category were examined in terms of distribution along the genome, minor allele frequency, Wrights fixation index (FST), individual load, and association to production traits.

ResultsOf the 46 million called variants, 28% were private (called in only one line) and 21% were widespread (called in all nine lines). Genomic regions with low recombination rate were enriched with private variants. Low-prevalence variants (called in one or a few lines only) were enriched for lower allele frequencies, lower FST, and putatively functional and regulatory roles (including loss-of-function and deleterious missense variants). Only a small subset of low-prevalence variants was found at intermediate allele frequencies and had large estimated effects on production traits. Individuals on average carried less private deleterious missense alleles than expected compared to other predicted consequence types. A small subset of low-prevalence variants with intermediate allele frequencies and higher FST were detected as significantly associated to the production traits and explained small fractions of phenotypic variance (up to 3.2%). These associations were tagged by other more widespread variants, including intergenic variants.

ConclusionsMost low-prevalence variants are kept at very low allele frequency and only a small subset contributed detectable fractions of phenotypic variance. Not accounting for low-prevalence variants is therefore unlikely to hinder across-breed analyses, in particular for genomic prediction of breeding values using reference populations of a different genetic background.


title: Transmission Dynamics of Human Herpesviruses and Other Blood DNA Viruses from Whole Genome Sequences of Families

abstract: 1While hundreds of thousands of human whole genome sequences (WGS) have been collected in the effort to better understand genetic determinants of disease, these whole genome sequences have rarely been used to study another major determinant of human health: the human virome. Using the unmapped reads from WGS of 1,000 families, we present insights into the human blood DNA virome. In addition to extensively cataloguing the viruses detected in WGS of human whole blood and lymphoblastoid cell lines, we use the family structure of our dataset to show that household drives transmission of many microbes. We also identify several cases of inherited chromosomally integrated herpes 6A and 6B and locate candidate integration sequences for these cases. We document genetic diversity within exogenous and integrated HHV species and within integration sites of HHV-6. Finally, in the first observation of its kind, we present evidence that suggests widespread de novo HHV-6B integration and HHV-7 episome replication in lymphoblastoid cell lines. These findings show that the unmapped read space of WGS may be a promising avenue for virology research.


title: Genetic mapping of flowering time and plant height in a maize Stiff Stalk MAGIC population

abstract:
The Stiff Stalk heterotic pool is a foundation of US maize seed parent germplasm and has been heavily utilized by both public and private maize breeders since its inception in the 1930s. Flowering time and plant height are critical characteristics for both inbred parents and their test crossed hybrid progeny. To study these traits, a six parent multiparent advanced generation intercross (MAGIC) population was developed including maize inbred lines B73, B84, PHB47 (B37 type), LH145 (B14 type), PHJ40 (novel early Stiff Stalk), and NKH8431 (B73/B14 type). A set of 779 doubled haploid lines were evaluated for flowering time and plant height in two field replicates in 2016 and 2017, and a subset of 689 and 561 doubled haploid lines were crossed to two testers, respectively, and evaluated as hybrids in two locations in 2018 and 2019 using an incomplete block design. Markers were derived from a Practical Haplotype Graph built from the founder whole genome assemblies and genotype-by-sequencing and exome capture-based sequencing of the population. Genetic mapping utilizing an update to R/qtl2 revealed differing profiles of significant loci for both traits between 636 of the DH lines and two sets of 571 and 472 derived hybrids. Genomic prediction was used to test the feasibility of predicting hybrid phenotypes based on the per se data. Predictive abilities were highest on direct models trained using the data they would predict (0.55 to 0.63), and indirect models trained using per se data to predict hybrid traits had slightly lower predictive abilities (0.49 to 0.55). Overall, this finding is consistent with the overlapping and non-overlapping significant QTL found within the per se and hybrid populations and suggests that selections for phenology traits can be made effectively on doubled haploid lines before hybrid data is available.

Core IdeasA multi-parent advanced generation intercross (MAGIC) mapping population was developed from six founder Stiff Stalk maize inbreds with commercial relevance. Genetic mapping utilizing an update to R/qtl2 was demonstrated for flowering and plant height traits.

Genetic mapping using maize inbred and hybrid information was compared and provided insight into trait expression in inbreds relative to heterotic testcross hybrids.


title: Identifying inputs to visual projection neurons in Drosophila lobula by analyzing connectomic data

abstract: Electron microscopy-based connectomes provide important insights into how visual circuitry of fruit fly Drosophila computes various visual features, guiding and complementing behavioral and physiological studies. However, connectomic analyses of lobula, a putative center of object-like feature detection, remains underdeveloped, largely because of incomplete data on the inputs to the brain region. Here, we attempted to map the columnar inputs into the Drosophila lobula neuropil by performing connectivity- and morphology-based clustering on a densely reconstructed connectome dataset. While the dataset mostly lacked visual neuropils other than lobula, which would normally help identify inputs to lobula, our clustering analysis successfully extracted clusters of cells with homogeneous connectivity and morphology, likely representing genuine cell types. We were able to draw a correspondence between the resulting clusters and previously identified cell types, revealing previously undocumented connectivity between lobula input and output neurons. While future, more complete connectomic reconstructions are necessary to verify the results presented here, they can serve as a useful basis for formulating hypotheses on mechanisms of visual feature detection in lobula.


title: A Split-GAL4 screen identifies novel sleep-promoting neurons in the Ventral Nerve Cord of Drosophila

abstract: As in the mammalian system, sleep in Drosophila is regulated by multiple brain regions. Among them, neurons projecting to the dorsal Fan-Shaped Body (dFB) have been intensively studied and the data suggest they play a critical role in sleep regulation. The 23E10-GAL4 driver is the most widely used tool to label and manipulate dFB neurons. Multiple studies have reported that activation of 23E10-GAL4 neurons promotes sleep. However, anatomical analyses revealed that 23E10-GAL4 labels 23-30 dFB neurons in the Drosophila brain and many non-dFB neurons in the brain and in the Ventral Nerve Cord (VNC), the fly equivalent of the spinal cord. To better understand the role of individual dFB neurons in sleep regulation, we undertook a Split-GAL4 screen to gain access to subsets of 23E10-GAL4 expressing cells. In this study, we report the discovery of two VNC cholinergic sleep-promoting neurons labeled by the 23E10-GAL4 driver.


title: CLEC5A and TLR2 are critical in SARS-CoV-2-induced NET formation and lung inflammation

abstract: Coronavirus-induced disease 19 (COVID-19) infects more than three hundred and sixty million patients worldwide, and people with severe symptoms frequently die of acute respiratory distress syndrome (ARDS). Autopsy demonstrates the presence of thrombosis and microangiopathy in the small vessels and capillaries. Recent studies indicated that excessive neutrophil extracellular traps (NETs) contributed to immunothrombosis, thereby leading to extensive intravascular coagulopathy and multiple organ dysfunction. Thus, understanding the mechanism of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-induced NET formation would be helpful to reduce thrombosis and prevent ARDS. It has been shown that sera from individuals with COVID-19 triggered NET release in vitro, and spleen tyrosine kinase (Syk) inhibitor R406 inhibited NETosis caused by COVID-19 plasma. However, the serum components responsible for NET formation are still unknown. In this study, we found that virus-free extracellular vesicles (EVs) from COVID-19 patients (COVID-19 EVs) induced robust NET formation via Syk-coupled C-type lectin member 5A (CLEC5A). Blockade of CLEC5A inhibited COVID-19 EVs-induced NETosis, and simultaneous blockade of CLEC5A and TLR2 further suppressed SARS-CoV-2-induced NETosis in vitro. Moreover, thromboinflammation and lung fibrosis were attenuated dramatically in clec5a-/-/tlr2-/- mice. These results suggest that COVID-19 EVs play critical roles in SARS-CoV-2-induced immunothrombosis, and blockade of CLEC5A and TLR2 is a promising strategy to inhibit SARS-CoV-2-induced intravascular coagulopathy and reduce the risk of ARDS in COVID-19 patients.


title: The impact of multigenerational high-fat diet feeding on the gut microbiome and host metabolism

abstract: Although human genetics partially explain the heritability of obesity and type 2 diabetes (T2D), the human gut microbiome also plays a significant role. While changes in human genetics at the population level occur only after many generations, the gut microbiome evolves over a shorter time span. The gut microbiome is also vertically transmitted across generations, therefore, changes in one generation can be passed on to subsequent generations. However, it is unknown whether the gut microbiome influences natural selection of its host under obesogenic pressure. Here, we show that C57BL/6 mice fed a high-fat diet (60% fat, HFD) over four generations develop resistance to obesity and the metabolic syndrome (MetS). Unexpectedly, the mice were increasingly leaner as well as more glucose tolerant and insulin sensitive across generations. This phenomenon was attributed to the most obese mice not yielding progenies, whereas the leanest mice successfully reproduced, and their offspring were also resistant to obesity. In other words, a population bottleneck was observed. Because all the mice were nearly genetically identical inbred C57BL/6J mice, the large variation in body weight gain in response to HFD feeding was likely independent of genetics. We explored whether microbial factors enriched in obesity-resistant mice promote healthier host metabolic phenotypes under HFD feeding, thereby contributing to the heterogeneity in body weight gain and providing an adaptive advantage to the host. Pearson correlation analysis revealed that body weight gain was positively correlated with Lactococcus lactis, as well as negatively correlated with Lactobacillus johnsonii and pathways for coenzyme A biosynthesis, amino acid biosynthesis (lysine, isoleucine, valine), and nucleotide biosynthesis (adenosine, guanosine). Overall, we observed multigenerational adaptation in the gut microbiome correlated with improved metabolism, yet further studies are needed to validate that these adaptations drive metabolic health.


title: Gut commensal bacteria enhance pathogenesis of a tumorigenic murine retrovirus

abstract: The influence of the microbiota on viral transmission and replication is well appreciated. However, its impact on retroviral pathogenesis outside of transmission/replication control remained unknown. Using Murine Leukemia Virus (MuLV), we found that some commensal bacteria promoted the development of leukemia induced by this retrovirus. The promotion of leukemia development by commensals was due to suppression of the adaptive immune response through upregulation of several negative regulators of immunity. These negative regulators included Serpinb9b and Rnf128, which are associated with a poor prognosis of some spontaneous human cancers. Upregulation of Serpinb9b was mediated by sensing of bacteria by NOD1/NOD2/RIPK2 pathway. This work describes a novel mechanism by which the microbiota enhances tumorigenesis within gut-distant organs and points at potential new targets for cancer therapy.


title: Stability and volatility shape the gut bacteriome and mycobiome dynamics in a pig model

abstract: The gut microbiome plays important roles in the maintenance of health and pathogenesis of diseases in the growing host. In order to fully comprehend the interplay of the gut microbiome and host, a foundational understanding of longitudinal bacteriome and mycobiome development is necessary. In this study, we evaluated enteric bacterial, fungal and host dynamics throughout the lifetime of commercial swine. We collected a total of 234 fecal samples from 9 pigs across 31 time points in 3 developmental stages (5 preweaning, 15 nursery, and 11 growth adult). We then performed 16S rRNA amplicon sequencing for bacterial profiles and qPCR for the fungus Kazachstania slooffiae. We identified distinct bacteriome clustering according to the host developmental stage, with the preweaning stage exhibiting low bacterial diversity and high volatility amongst samples. We further recovered clusters of bacterial populations that were considered core, transient and increasing throughout the host lifetime, suggesting distinct yet important roles by which these differing bacterial population clusters played in the different host stages. Kazachstania slooffiae was absent in the preweaning stage but peaked during the nursery stage of the host. We determined that all host growth stages contained negative correlations between K. slooffiae and bacterial genera, with only the growth adult stage containing positive correlates. The lack of positive correlates and shared K. slooffiae-bacteria interactions between stages warrants future research into the interactions amongst these kingdoms for host health. This research is foundational for understanding how the bacteriome and mycobiome develop singularly, as well as within a complex ecosystem in the hosts gut environment.


title: Imaging minimal bacteria at the nanoscale: a reliable and versatile process to perform Single Molecule Localization Microscopy in mycoplasmas

abstract:
Mycoplasmas are the smallest free-living organisms. These bacteria are important models for both fundamental and Synthetic Biology, owing to their highly reduced genomes. They are also relevant in the medical and veterinary fields, as they are pathogenic of both humans and most livestock species. Mycoplasma cells have minute sizes, often in the 300-800 nanometers range. As these dimensions are close to the diffraction limit of visible light, fluorescence imaging in mycoplasmas is often poorly informative. Recently developed "Super-Resolution Imaging" techniques can break this diffraction limit, improving the imaging resolution by an order of magnitude and offering a new nanoscale vision of the organization of these bacteria. These techniques have however not been applied to mycoplasmas before. Here, we describe an efficient and reliable protocol to perform Single-Molecule Localization Microscopy (SMLM) imaging in mycoplasmas. We provide a polyvalent transposon-based system to express the photo-convertible fluorescent protein mEos3.2, enabling Photo-Activated Localization Microscopy (PALM) in most Mycoplasma species. We also describe the application of direct STochastic Optical Reconstruction Microscopy (dSTORM). We showcase the potential of these techniques by studying the subcellular localization of two proteins of interest. Our work highlights the benefits of state-of-the-art microscopy techniques for mycoplasmology and provides an incentive to further the development SMLM strategies to study these organisms in the future.

ImportanceMycoplasmas are important models in biology, as well as highly problematic pathogens in the medical and veterinary fields. The very small size of these bacteria, well below the micron, limits the usefulness of traditional fluorescence imaging methods as their resolution limit is similar to the dimensions of the cells. Here, to bypass this issue, we established a set of state-of-the-art "Super-Resolution Microscopy" techniques in a wide range of Mycoplasma species. We describe two strategies: PALM, based on the expression of a specific photo-convertible fluorescent protein; and dSTORM, based on fluorophore-coupled antibody labeling. With these methods, we successfully performed single-molecule imaging of proteins of interest at the surface of the cells and in the cytoplasm, at lateral resolutions well below 50 nanometers. Our work paves the way toward a better understanding of mycoplasmas biology through imaging of subcellular structures at the nanometer scale.


title: The new archaeal order Lutiacidiplasmatales reveals convergent evolution in Thermoplasmatota

abstract: The archaeal Terrestrial Miscellaneous Euryarchaeota Group (TMEG) has been identified in various environments, and the single genome investigated thus far suggests that these organisms are anaerobic sulfite reducers. We assembled 35 new TMEG genomes that, based on genome analysis, appear to possess aerobic and facultative anaerobic lifestyles and may oxidise rather than reduce sulfite. We propose naming this order (representing 16 genera) "Lutiacidiplasmatales" due to their occurrence in various acidic environments and placement within the phylum Thermoplasmatota. A phylum-level analysis revealed that Thermoplasmatota evolution had been punctuated by several periods of high levels of novel gene family acquisition. Several essential metabolisms, such as aerobic respiration and acid tolerance, were likely acquired independently by divergent lineages through convergent evolution rather than inherited from a common ancestor. Ultimately, this study describes the terrestrially prevalent Lutiacidiciplasmatales and indicates convergent evolution as an important evolutionary driving force in archaeal lineages with complex histories.


title: Antimicrobial resistance and virulence characteristics of Klebsiella pneumoniae isolates in Kenya

abstract:
Klebsiella pneumoniae is a globally significant opportunistic pathogen causing healthcare-associated and community-acquired infections. This study examined the epidemiology and the distribution of resistance and virulence genes in clinical K. pneumoniae strains in Kenya. Eighty-nine K. pneumoniae isolates were collected over six years from five counties in Kenya and were analyzed using whole genome sequencing and bioinformatics. These isolates were obtained from community-acquired (62/89) and healthcare-associated infections (21/89), and the hospital environment (6/89). Genetic analysis revealed the presence of blaNDM-1 and blaOXA-181 carbapenemase genes and the armA and rmtF genes known to confer pan-aminoglycoside resistance. The most abundant extended-spectrum beta-lactamase genes identified were blaCTX-M-15 (36/89), blaTEM (35/89), and blaOXA (18/89). In addition, one isolate had a mobile colistin resistance gene (mcr-8). Fluoroquinolone resistance-conferring mutations in gyrA and parC genes were also observed. The most notable virulence factors were those associated with hyper-virulence (rmpA/A2 and magA), yersiniabactin (ybt), salmochelin (iro), and aerobactin (iuc and iutA). Thirty-eight distinct sequence types were identified, including known global lineages ST14, ST15, ST147, and ST307, and a regional clone ST17 implicated in regional outbreaks. In addition, this study genetically characterized two potential hypervirulent isolates and two community-acquired ST147 high-risk clones that contained carbapenemase genes, yersiniabactin, and other multidrug resistance genes. These results demonstrate that the resistome and virulome of Kenyan clinical and hospital environmental K. pneumoniae isolates are diverse. The reservoir of high risk-clones capable of spreading resistance and virulence factors have the potential to cause unmanageable infection outbreaks with high morbidity and mortality.

AUTHOR SUMMARYKlebsiella pneumoniae is one of the human-disease-causing bacteria that easily acquires and spreads antibiotic resistance genes and is thus a serious threat to human health. We studied both the antibiotic resistance genes and the genes it uses to cause disease (virulence). Forty-two percent of our isolates were multidrug resistant (MDR). They carried several resistance and virulence genes bound in mobile circular DNA molecules called plasmids which easily migrate and spread the genes between bacteria. We identified 38 distinct K. pneumoniae strains (STs) distributed within the study sites. Fifteen isolates were classified under the groups of K. pneumoniae strains known to cause global infection outbreaks such as ST14, ST15 and ST147 collected from Nairobi and Kisumu, hotspot areas for spread of resistance. In particular, two ST147 isolates were resistant to carbapenems and one isolate to colistin, which are last line antibiotics. We also identified two isolates with the potential to cause high levels of disease. We concluded that the presence of highly resistant and virulent strains in the hospital and community demonstrates a need for the continuous monitoring and management of MDR K. pneumoniae infections to prevent disease outbreaks that are difficult to control and that lead to high death rate.


title: Why SARS-CoV-2 Omicron variant is milder? A single high-frequency mutation of structural envelope protein matters.

abstract: SARS-CoV-2 Omicron variant is highly transmissible and extensive morbidity, which has raised concerns for antiviral therapy. In addition, the molecular basis for the attenuated pathogenicity and replication capacity of Omicron remains elusive. Here, we report for the first time that a high-frequency mutation T9I on 2-E of SARS-CoV-2 variant Omicron forms a non-selective ion channel with abolished calcium permeability and reduced acid sensitivity compared to the WT channel. In addition, T9I caused less cell death and a weaker cytokine production. The channel property changes might be responsible for the Omicron variant releases less efficiently and induces a comparatively lower level of cell damage in the infected cells. Our study gives valuable insights into key features of the Omicron variant, further supporting 2-E is a promising drug target against SARS-CoV-2 and providing critical information for the COVID-19 treatment.


title: USP22 controls type III interferon signaling and SARS-CoV-2 infection through activation of STING

abstract: Pattern recognition receptors (PRRs) and interferons (IFNs) serve as essential antiviral defense against SARS-CoV-2, the causative agent of the COVID-19 pandemic. Type III IFN (IFN-{lambda}) exhibit cell-type specific and long-lasting functions in autoinflammation, tumorigenesis and antiviral defense. Here, we identify the deubiquitinating enzyme USP22 as central regulator of basal IFN-{lambda} secretion and SARS-CoV-2 infections in native human intestinal epithelial cells (hIECs). USP22-deficient hIECs strongly upregulate genes involved in IFN signaling and viral defense, including numerous IFN-stimulated genes (ISGs), with increased secretion of IFN-{lambda} and enhanced STAT1 signaling, even in the absence of exogenous IFNs or viral infection. Interestingly, USP22 controls basal and 23-cGAMP-induced STING activation and loss of STING reversed STAT activation and ISG and IFN-{lambda} expression. Intriguingly, USP22-deficient hIECs are protected against SARS-CoV-2 infection, viral replication and the formation of de novo infectious particles, in a STING-dependent manner. These findings reveal USP22 as central host regulator of STING and type III IFN signaling, with important implications for SARS-CoV-2 infection and antiviral defense.


title: Conformational transitions of the mitotic adaptor Spindly underlie its interaction with Dynein and Dynactin

abstract: Cytoplasmic Dynein 1, or Dynein, is a microtubule minus-end directed motor. Dynein motility requires Dynactin and a family of activating adaptors that stabilize the Dynein-Dynactin complex and promote regulated interactions with cargo in space and time. How activating adaptors limit Dynein activation to specialized subcellular locales is unclear. Here, we reveal that Spindly, a mitotic Dynein adaptor at the kinetochore corona, exists natively in a closed conformation that occludes binding of Dynein-Dynactin to its CC1 box and Spindly motif. A structure-based analysis identified various mutations promoting an open conformation of Spindly that binds Dynein-Dynactin. A region of Spindly downstream from the Spindly motif and not required for cargo binding faces the CC1 box and stabilizes the intramolecular closed conformation. This region is also required for robust kinetochore localization of Spindly, suggesting that kinetochores promote Spindly activation to recruit Dynein. This mechanism may be paradigmatic for Dynein activation by other adaptors at various cellular locales.

category: biochemistry


title: Cyclization studies of Japanese encephalitis virus non-coding RNA terminal regions.

abstract: Many flaviviruses such as Dengue and West Nile virus undergo essential long-range interactions of their 5 and 3 terminal regions (TRs), mediated by a conserved complementary cyclization sequence. However, we lack insights into such long-range interactions for the Japanese Encephalitis virus (JEV). Here, we utilized an extensive, multi-faceted approach involving computational and biophysical tools. We performed multi-angle light scattering (SEC-MALS) to determine absolute molecular weights of JEV TRs, and their complex concluding they form a 1:1 complex and corroborated this interaction using analytical ultracentrifugation (AUC). The microscale thermophoresis (MST) experiments demonstrated that the 5 and 3 TR of JEV interact with nM affinity, which is significantly reduced without the conserved cyclization sequence. To our knowlwege, this is the first study representing the application of three key biophysical methods (AUC, MST and SEC-MALS) to study RNA-RNA interactions. Furthermore, we performed computational kinetic analyses corroborating our MST studies showing the essential role of the cyclization sequence in the RNA-RNA interaction. The binding affinity of this biologically critical event is a vital pharmacological feature that can influence potential competitive inhibition by therapeutics. This evidence can also influence pharmaceutical interventions aimed at inhibiting the conserved flavivirus cyclization, thus, interrupting replication across the flavivirus family.


title: RNase H-based analysis of synthetic mRNA 5-prime cap incorporation

abstract: Advances in mRNA synthesis and lipid nanoparticles technologies have helped make mRNA therapeutics and vaccines a reality. The 5 cap structure is a crucial modification required to functionalize synthetic mRNA for efficient protein translation in vivo and evasion of cellular innate immune responses. The extent of 5 capping is one of the critical quality attributes in mRNA manufacturing. RNA cap analysis involves multiple steps: generation of pre-defined short fragments from the 5 end of the kilobase-long synthetic mRNA molecules using RNase H or a DNAzyme, 5 cleavage products enrichment, and LC-MS intact mass analysis. In this communication, we describe 1) our results on the sequence preference of RNase H cleavage and a framework to design site-specific RNA cleavage; 2) a method to fluorescently label the RNase H cleavage fragments for readouts such as easily accessible urea-PAGE or high throughput capillary electrophoresis; 3) a simplified method for post-RNase H purification using desthiobiotinylated oligonucleotides and streptavidin magnetic beads followed by elution using water. By providing a design framework for RNase H-based RNA 5 cap analysis using less resource-intensive analytical methods, we hope to make RNA cap analysis more accessible to the scientific community.


title: A natural fusion of flavodiiron, rubredoxin, and NADH:rubredoxin oxidoreductase domains is the highly efficient water-forming oxidase of T. vaginalis

abstract: Microaerophilic pathogens such as Giardia lamblia and Trichomonas vaginalis have robust oxygen consumption systems to detoxify oxygen and maintain the intracellular redox balance. This oxygen consumption is a result of the H2O-forming NADH oxidase activity of two distinct flavin-containing systems: H2O-forming NADH oxidases (NOXes) and multicomponent flavodiiron proteins (FDPs). Both systems are not membrane-bound and recycle NADH into oxidized NAD+ while simultaneously removing O2 from the local environment, making them crucial for the survival of human microaerophilic pathogens. In this study, using bioinformatic and biochemical analysis, we show that T. vaginalis lacks a NOX-like enzyme, and instead harbors three proteins that are very close in their amino acid sequence and represent a natural fusion between N-terminal FDP, central rubredoxin and C-terminal NADH:rubredoxin oxidoreductase domains. We demonstrate that this natural fusion protein with fully populated flavin redox centers unlike a "stand-alone" FDP (also present in T. vaginalis), directly accepts reducing equivalents of NADH to catalyze the four-electron reduction of O2 to water within a single polypeptide and with an extremely high turnover. Using single particle electron cryo-microscopy (cryo-EM) we present structural insight into the spatial organization of the FDP core within this multidomain fusion protein. Our studies represent an important addition to our understanding of systems that allow human protozoan parasites to maintain their optimal redox balance and survive transient exposure to oxic conditions.


title: Effects of calorie restriction on reactive oxygen species production by mitochondrial reverse electron transport, mitochondrial permeability transition pore, and beta-adrenergic stimulation during cardiac hypertrophy

abstract: Calorie restriction is a nutritional intervention that reproducibly protects against the maladaptive consequences of cardiovascular diseases. Pathological cardiac hypertrophy leads to cellular growth, dysfunction (with mitochondrial dysregulation), and oxidative stress. The mechanisms behind the cardiovascular protective effects of calorie restriction are still under investigation. In this study, we addressed the impact of calorie restriction on mitochondria, oxidative stress markers, and {beta}-adrenergic signaling during cardiac hypertrophy. This dietetic intervention prevented cardiac protein elevation, decreased atrial natriuretic peptide levels, and blocked the increase in heart weight per tibia length index seen in isoproterenol-induced cardiac hypertrophy. Our data suggest that inhibition of cardiac pathological growth by calorie restriction is accompanied by a lower mitochondrial reactive oxygen species formation and improved mitochondrial content. We also found that superoxide dismutase and glutathione peroxidase activities negatively correlate with cardiac hypertrophy. Calorie restriction also attenuated the opening of the Ca2+-induced mitochondrial permeability transition pore in mitochondria isolated from isoproterenol-treated mice. Isoproterenol (a {beta}-agonist) increases cardiac rate (chronotropic response) and force of contraction (inotropic response). Given the nature of cardiac hypertrophy induction by isoproterenol, we tested whether calorie restriction could change the cardiac {beta}-adrenergic sensitivity. Using isolated rat hearts in a langendorff system, we found that calorie restriction mice (similar to controls) have preserved {beta}-adrenergic signaling. On the flipside, hypertrophic hearts (treated for seven days with isoproterenol) were insensitive to {beta}-adrenergic activation using isoproterenol (50 nM). Despite protecting against cardiac hypertrophy, calorie restriction did not alter the lack of responsiveness to isoproterenol of isolated hearts harvested from isoproterenol-treated rats. These results suggest (through a series of mitochondrial, oxidative stress, and cardiac hemodynamic studies) that calorie restriction possesses beneficial effects against hypertrophic cardiomyopathy. However, it may lack effects on some of the hypertrophic consequences, such as {beta}-adrenergic signaling repression.


title: Chemically modified dsRNA induces RNAi effects in insects in vitro and in vivo: A potential new tool for improving RNA-based plant protection

abstract: Global agriculture loses over $100 billion of produce annually to crop pests such as insects. Many of these crop pests either have no current means of control or have developed resistance against chemical pesticides. Long dsRNAs are capable of inducing RNA interference (RNAi) in insects and are emerging as novel highly selective alternatives for sustainable insect management strategies. However, there are significant challenges associated with RNAi efficacy in insects. In this study, we synthesised a range of chemically modified long dsRNA in an approach to improve nuclease resistance and RNAi efficacy in insects. The results showed that dsRNA containing phosphorothioate modifications demonstrated increased resistance to southern green stink bug saliva nucleases. Phosphorothioate and 2-fluoro modified dsRNA also demonstrated increased resistance to degradation by soil nucleases and increased RNAi efficacy in Drosophila melanogaster cell cultures. In live insects, chemically modified long dsRNA successfully resulted in mortality in both stink bug and corn rootworm. The results provide further mechanistic insight of RNAi efficacy dependence on modifications in the sense or antisense strand of the dsRNA in insects and demonstrate for the first time that RNAi can successfully be triggered by chemically modified long dsRNA in insect cells or live insects.


title: Design and development of potent h-ACE2 derived peptide mimetics in SARS-CoV-2 Omicron variant therapeutics

abstract: The pandemic of COVID-19 has become the global health challenge due to the emergence of new variants. The Receptor binding domain (RBD) of spike protein that makes direct interaction with ACE-2 has shown unique mutated residues in most of the variants of concern (VOC). Recently WHO declared the Omicron (B.1.1.529) as VOC considering it as a highly mutated variant which includes a total of 60 mutations out of which 15 mutations occurred in RBD region of SARS-CoV-2. Inhibition of Protein-protein (Omicron RBD-h-ACE2) interaction was already proved to inhibit the viral infection. In this study, by using molecular dynamic simulations efforts are made to explore the atomistic details of Omicron RBD-h-ACE2 interaction. Based on MD simulations, h-ACE2 motif is found to be interacting with omicron RBD domain. Interaction analysis had provided key residues interacting with Omicron-RBD that helped to extract h-ACE2 peptide. Here, rational design of the peptides that have resemblance with h-ACE2 is done and the peptide library is subjected for inhibition studies against Omicron-RBD. The current study helped to identify the significant peptides that can inhibit Omicron-RBD. Altogether the performed studies will provide an opportunity to develop potential therapeutic peptidomimetics effective against Omicron variant of SARS-CoV-2.


title: Patterns of Volatility Across the Spike Protein Accurately Predict the Emergence of Mutations within SARS-CoV-2 Lineages

abstract:
New lineages of SARS-CoV-2 are constantly emerging. They contain mutations in the spike glycoprotein that can affect virus infectivity, transmissibility, or sensitivity to vaccine-elicited antibodies. Here we show that the emergence of new spike variants is accurately predicted by patterns of amino acid variability (volatility) in small virus clusters that phylogenetically-precede or chronologically-predate such events. For each spike position, volatility within the virus clusters, volatility at adjacent positions on the three-dimensional structure of the protein, and volatility across the network of co-volatile sites describe its likelihood for mutations. By combining these variables, early-pandemic sequences accurately forecasted mutations in lineages that appeared 6-13 months later. The patterns of mutations in variants Alpha and Delta, as well as the recently-appearing variant Omicron were also predicted remarkably well. Importantly, probabilities assigned to spike positions for within-lineage mutations were lineage-specific, and accurately forecasted the observed changes. Sufficient antecedent warning of the imminent changes in SARS-CoV-2 lineages will allow design of immunogens that address their specific antigenic properties.

SIGNIFICANCENew variants of SARS-CoV-2 continue to emerge in the population. Due to mutations in the spike protein, some variants exhibit partial resistance to therapeutics and to the immunity provided by COVID-19 vaccines. Thus, there is a need for accurate tools to forecast the appearance of new virus forms in the population. Here we show that patterns of amino acid variability across the spike protein accurately predict the mutational patterns that appeared within SARS-CoV-2 lineages with considerable advance warning time. Interestingly, mutation probabilities varied greatly between lineages, most notably for critical sites in the receptor-binding domain of spike. The high predictive capacity of the model allows design of vaccines that address the properties of variants expected to emerge in the future.


title: A new fold in TANGO1 evolved from SH3 domains for the export of bulky cargos

abstract: Bulky cargos like procollagens, apolipoproteins, and mucins exceed the size of conventional COPII vesicles. During evolution a process emerged in metazoans, predominantly governed by the TANGO1 protein family, that organizes cargo at the exit sites of the endoplasmic reticulum and facilitates export by the formation of tunnel-like connections between the ER and Golgi. Cargorecognition appears to be mediated by an SH3-like domain, however, just how the vastly different cargos are recognized remains elusive. Based on structural and dynamic data as well as interaction studies from NMR spectroscopy presented here, we show that the luminal cargo-recognition domain of TANGO1 adopts a new functional fold for which we suggest the term MOTH (MIA, Otoraplin, TALI/TANGO1 homology) domain. Also, differences in the structural properties within the domain family suggest fundamentally different mechanisms of cargo-recognition in vertebrates and invertebrates. Similarly, in vertebrates, it is proposed that cargo-specificity is mediated by structural differences within the vertebrate TANGO1 and TALI MOTH domains themselves.


title: Chronic alcohol intake regulates expression of SARS-CoV2 infection-relevant genes in an organ-specific manner

abstract: Chronic alcohol consumption and alcohol use disorder (AUD) have a tremendous impact on the patients psychological and physiological health. There is some evidence that chronic alcohol consumption influences SARS-CoV2 infection risk, but the molecular mechanism is unknown. Here, we generated expression data of SARS-CoV2 infection relevant genes (Ace2, Tmprss2 and Mas) in different organs in rat models of chronic alcohol exposure and alcohol dependence. ACE2 and TMPRSS2 represent the virus entry point whereas Mas is activating the anti-inflammatory response once the cells are infected. Across three different chronic alcohol test conditions, we found a consistent upregulation of Ace2 in the lung, which is the most affected organ in Covid-19 patients. Other organs such as liver, ileum, kidney, heart, and the brain showed also up-regulation of Ace2 and Mas but in a less consistent manner across the different animal models, while Tmprss2 was unaffected in all conditions. We suggest that alcohol-induced up-regulation of Ace2 can lead to an elevated stochastic probability of cellular virus entry and may thus confer a molecular risk factor for a SARS-CoV2 infection.

category: pharmacology and toxicology


title: Metabolic dyshomeostasis induced by SARS-CoV-2 structural proteins reveals immunological insights into viral olfactory interactions

abstract: One of the most common symptoms in COVID-19 is a sudden loss of smell. SARS-CoV-2 has been detected in the olfactory bulb (OB) from animal models and sporadically in COVID-19 patients. To decipher the specific role over the SARS-CoV-2 proteome at olfactory level, we characterized the in-depth molecular imbalance induced by the expression of GFP-tagged SARS-CoV-2 structural proteins (M, N, E, S) on mouse OB cells. Transcriptomic and proteomic trajectories uncovered a widespread metabolic remodeling commonly converging in extracellular matrix organization, lipid metabolism and signaling by receptor tyrosine kinases. The molecular singularities and specific interactome expression modules were also characterized for each viral structural factor. The intracellular molecular imbalance induced by each SARS-CoV-2 structural protein was accompanied by differential activation dynamics in survival and immunological routes in parallel with a differentiated secretion profile of chemokines in OB cells. Machine learning through a proteotranscriptomic data integration uncovered TGF-beta signaling as a confluent activation node by the SARS-CoV-2 structural proteome. Taken together, these data provide important avenues for understanding the multifunctional immunomodulatory properties of SARS-CoV-2 M, N, S and E proteins beyond their intrinsic role in virion formation, deciphering mechanistic clues to the olfactory inflammation observed in COVID-19 patients.

category: systems biology


title: Scale of analysis drives the observed ratio of spatial to non-spatial variance in microbial water quality: insights from two decades of citizen science data

abstract: While fecal indicator bacteria (FIB) testing is used to monitor surface waters for potential health hazards, recent studies report substantial variation in FIB levels and that observed variation appeared dependent on scale of analysis (SOA). Citizen science data and random effects models were used to quantify variance in FIB levels attributable to spatial versus temporal factors. Separately, Bayesian models were used to quantify the ratio of spatial to nonspatial variance in FIB levels, and identify associations between environmental factors and FIB levels. Separate analyses were performed for each stream, lake, and watershed as well as at the state-level (three SOAs). As SOA increased (from waterway to watershed to statewide models), variance attributable to spatial sources generally increased and variance attributable to temporal sources generally decreased. While relationships between FIB levels and environmental factors, such as flow conditions, were constant across SOA, the effect of land cover was both highly dependent on SOA and consistently smaller than the effect of outfalls. This study demonstrates the importance of scale when designing monitoring programs or using FIB monitoring to inform management. Moreover, these data represent a comprehensive survey of water quality in Upstate NY, and the study highlights a valuable publicly available database.


title: Class II UvrA protein Ecm16 requires ATPase activity to render resistance against echinomycin

abstract: II.Bacteria use various strategies to become antibiotic resistant. The molecular details of these strategies are not fully understood. We can increase our understanding by investigating the same strategies found in antibiotic-producing bacteria. In this work, we characterize the self-resistance protein Ecm16 encoded by echinomycin-producing bacteria. Ecm16 is a structural homolog of the Nucleotide Excision Repair (NER) protein UvrA. Expression of ecm16 in the heterologous system Escherichia coli was sufficient to render resistance against echinomycin. Ecm16 preferentially binds double-stranded DNA over single-stranded DNA and is likely to primarily interact with the backbone of DNA using a nucleotide-independent binding mode. Ecm16s binding affinity for DNA increased significantly when the DNA is intercalated with echinomycin. Ecm16 can repair echinomycin-induced DNA damage independently of NER. Like UvrA, Ecm16 has ATPase activity and this activity is essential for Ecm16s ability to render echinomycin resistance. Notably, UvrA and Ecm16 were unable to complement each others function. Increasing the cellular levels of UvrA in E. coli was insufficient to render echinomycin resistance. Similarly, Ecm16 was unable to repair DNA damage that is specific to UvrA. Together, our findings identify new mechanistic details of how a refurbished DNA repair protein Ecm16 can specifically render resistance to the DNA intercalator echinomycin. Our results, together with past observations, suggest a model where Ecm16 recognizes double helix distortions caused by echinomycin and repairs the problem independently of NER.


title: Microbiomes of the bloom-forming alga, Phaeocystis globosa, are stable, consistently recruited communities with symbiotic and opportunistic modes

abstract: Phaeocystis is a cosmopolitan, bloom-forming phytoplankton genus that contributes significantly to global carbon and sulfur cycles. During blooms, Phaeocystis species produce large carbon-rich colonies, thus creating a unique interface for bacterial interactions. While bacteria are known to interact with phytoplankton--e.g., they promote growth by producing phytohormones and vitamins--such interactions have not been shown for Phaeocystis. Therefore, we investigated the composition and function of P. globosa microbiomes. Specifically, we tested whether microbiome compositions are consistent across individual colonies from four P. globosa strains, whether similar microbiomes are re-recruited after antibiotic treatment, and how microbiomes affect P. globosa growth under limiting conditions. Results illuminated a core colonial P. globosa microbiome--including bacteria from the orders Alteromonadales, Burkholderiales, and Rhizobiales--that was re-recruited after microbiome disruption. Consistent microbiome composition and recruitment is indicative that P. globosa microbiomes are stable-state systems undergoing deterministic community assembly and suggests there are specific, beneficial interactions between Phaeocystis and bacteria. Growth experiments with axenic and nonaxenic cultures demonstrated that microbiomes allowed continued growth when B-vitamins were withheld, but that microbiomes accelerated culture collapse when nitrogen was withheld. In sum, this study reveals interactions between Phaeocystis colonies and microbiome bacteria that could influence large-scale phytoplankton bloom dynamics and biogeochemical cycles.


title: Intracellular flow cytometry complements RT-qPCR detection of circulating SARS-CoV-2 variants of concern

abstract:
Despite the efficacy of current vaccines against SARS-CoV-2, the spread of the virus is still not under control, as evidenced by the ongoing circulation of the highly contagious SARS-CoV-2 Omicron variant. Basic and antiviral research on SARS-CoV-2 relies on cellular assays of virus replication in vitro. In addition, accurate detection of virus-infected cells and released virus particles is needed to study virus replication and to profile new candidate antiviral drugs. Here, by flow cytometry, we detect SARS-CoV-2 infection at single cell level and distinguish infected Vero E6 cells from uninfected bystander cells. Furthermore, based on the viral nucleocapsid expression, subpopulations of infected cells that are in an early or late phase of viral replication can be differentiated. Importantly, this flow cytometric technique complements RT-qPCR detection and can be applied to all current SARS-CoV-2 variants of concern, including the highly mutated Omicron variant.

Method summaryThis study describes the characterization of SARS-CoV-2 infected cells using intracellular flow cytometric viral nucleocapsid staining that complements RT-qPCR quantification of viral RNA. The technique makes it possible to distinguish between infected cells in the early (low N) or late phase (high N) of viral replication. It can also be applied to the different variants of concern of SARS-CoV-2, including the Omicron variant.


title: Structural basis of streptomycin off-target binding to human mitoribosome

abstract: The ribosome in mitochondria regulates cellular energy production, and its deactivation is associated with pathologies and ageing. Inhibition of human mitoribosome can be caused by antimicrobial off-target binding, which leads to clinical appearances. The anti-tuberculosis drug aminoglycoside streptomycin targets the small subunit and was shown to be coupled with a bilateral decreased visual acuity with central scotomas and an altered mitochondrial structure. Previously, we reported mitochondria-specific aspects of translation related to specialties of the human mitoribosome (Aibara et al., 2020). In this Research advance article, we report 2.23-[A] resolution structure of the human mitoribosomal small subunit in complex with streptomycin. The structural data reveals new details of the streptomycin interactions, including specific water molecules and metal ions involved in the coordination. The density for the streptose moiety reveals that previously modeled aldehyde group appears as a loosely bound density, and the hydroxyl group is not resolved. The density replacing the aldehyde group is within hydrogen bonding distance of four phosphate groups of rRNA, suggesting that the ribosome-bound streptomycin is likely to be in the hydrated gem-diol form rather than in the free aldehyde form. Since streptomycin is a widely used drug for treatment, the newly resolved fine features can serve as determinants for targeting.

category: molecular biology


title: Ddp1 cooperates with Ppx1 to counter a stress response initiated by non-vacuolar polyphosphate

abstract: In diverse cells from bacterial to mammalian species, inorganic phosphate is stored in long chains called polyphosphates (polyP). These near universal polymers, ranging from 3 to thousands of phosphate moieties in length, are associated with molecular functions including energy homeostasis, protein folding, and cell signaling. In many cell types, polyphosphate is concentrated in subcellular compartments or organelles. In the budding yeast S. cerevisiae, polyP synthesis by the membrane-bound VTC complex is coupled to its translocation into the lumen of the vacuole, a lysosome-related organelle, where it is stored at high concentrations. In contrast, ectopic expression of bacterial polyphosphate kinase, PPK, results in the toxic accumulation of polyP outside of the vacuole. In this study, we used label-free mass spectrometry to investigate the mechanisms underlying this toxicity. We find that PPK expression results in the activation of a stress response mediated in part by the Hog1 and Yak1 kinases, and Msn2/Msn4 transcription factors. This response is countered by the combined action of the Ddp1 and Ppx1 polyphosphatases that function together to counter polyP accumulation and downstream toxicity. In contrast, ectopic expression of previously proposed mammalian polyphosphatases did not impact PPK-mediated toxicity in this model, suggesting either that these enzymes do not function directly as polyphosphatases in vivo or that they require co-factors unique to higher eukaryotes. Our work provides a mechanistic explanation for why polyP accumulation outside of lysosome-related organelles is toxic. Further, it serves as a resource for exploring how polyP may impact conserved biological processes at a molecular level.