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McNair, K.

Publications and source records attributed to McNair, K..

13 recordsLinked to original sources

Screening metatranscriptomes for ultrastable RNA secondary structures reveals hidden bacteriophages and novel capsid nanomaterials

Metatranscriptomics has transformed our view of RNA bacteriophage diversity, revealing vast numbers of single-stranded RNA (ssRNA) phages whose protein capsids can be engineered for biotechnology applications. However, many ssRNA phages remain hidden from current detection methods, which require protein-level similarity to known phages. Here we show that RNA structure provides an additional signal for the detection of ssRNA phages in metatranscriptomes, including hidden phages missed by prior protein-based methods. By computationally folding each contig and screening for exceptionally stable RNA secondary structures, we find evidence of thousands of previously unrecognized phages encoding novel coat proteins. We express a library of 12,000 such coat proteins in E. coli and find that most assemble into nuclease-resistant capsids. We determine the 3D structure of one such capsid by cryo-electron microscopy and demonstrate that it can be disassembled and reassembled in vitro to package heterologous RNA--a key step toward repurposing these particles as RNA delivery vehicles. We compile the newly discovered ssRNA phages with previously known ones into a database that contains sequence and structural information for over 460,000 unique RNA molecules and over 100,000 distinct coat proteins, providing a comprehensive resource for microbiology and nanomaterials research.

biochemistry↗

Multimodal spatial transcriptomics determines repeat expansion, huntingtin aggregation, and selective cortical neuron loss in Huntington Disease

Huntingtons disease (HD) is caused by CAG expansion in HTT, yet how somatic repeat instability and huntingtin aggregation relate to selective cell loss in the human brain remains unclear. We have developed a multimodal spatial transcriptomics approach that enables defining transcriptional programs with subcellular resolution, somatic CAG repeat lengths, and six other pathology marks including huntingtin aggregates in every cell of intact brain sections. Imaging 428,173 cells in HD cortex revealed selective vulnerability: L5-6 NP and L6b deep-layer excitatory neurons undergo >50% loss, closely linked to very large (>380{+/-}55) somatic expansions. Intranuclear aggregation was most prevalent at intermediate somatic repeat expansion (220-300 CAGs) and was accompanied by broader transcriptional changes. In contrast, chandelier and somatostatin+ inhibitory interneurons are lost despite only modest repeat expansion or aggregation. These data provide a comprehensive resource and establish a broadly applicable framework for connecting repeat expansion and protein pathology across diverse cell types. Short Bullet pointsO_LIDevelopment of a novel, multimodal spatial transcriptomics platform enables definition of RNA transcriptomes with subcellular resolution, somatic repeat expansions, and protein accumulation in cells within tissue sections C_LIO_LIGeneration of two complementary datasets for HD and control cortex: 428,173 cells to quantify comprehensively cell-type vulnerability, and a deeper multimodal dataset in which CAG repeat expansion, huntingtin aggregation, six additional pathological readouts, and expression of 1,128 genes were measured in 185,721 cells, providing a comprehensive resource for the neurodegeneration community. C_LIO_LIDeep layer excitatory neuron loss (L5-6 NP and L6b) was associated with very large somatic CAG expansions (>380{+/-}55), while selective inhibitory neuron loss (chandelier and somatostatin interneurons) occurred with modest CAG repeat expansion or huntingtin intranuclear aggregation C_LIO_LIIntranuclear aggregation, not somatic repeat expansion, was more predictive of transcriptional changes, including chromatin remodeling and RNA export factors C_LI

neuroscience↗

Decoding the dynamics of cognitive control: Insights from reach movements and electroencephalography

The congruency sequence effect (CSE) refers to improved performance in conflict tasks, such as the Eriksen flanker task, when the congruency of the current trial matches that of the preceding one. Although widely attributed to dynamic adjustments in cognitive control, the neural mechanisms and temporal dynamics underlying this effect remain poorly understood. Here, we combined a release-and-press flanker task with EEG decoding to examine how trial congruency and response type shape behavior and brain activity in healthy adults. Behaviorally, the CSE emerged only when responses repeated, highlighting the dominant role of stimulus-response binding over abstract control mechanisms. Neural decoding mirrored the CSE: current-trial congruency was more reliably decoded on repeated-response trials following congruent versus incongruent trials. This neural CSE was stimulus-locked, occurred between 450-550ms post-stimulus onset, and was driven by theta-band activity. More broadly, congruency decoding was particularly robust over frontal channels while cross-temporal generalization indicated transient, sequential neural representations underlying control signals. Together, these findings demonstrate that both behavioral and neural signatures of the CSE are tightly constrained by response repetition and emerge within a narrow temporal window. By integrating reach-based measures with multivariate EEG analyses, this study provides a fine-grained account of when, where, and under what conditions control-related signals unfold after conflict.

neuroscience↗

Establishing thresholds for cytokine storm and defining their relationship to disease severity in respiratory viral infections

Previous studies have identified cytokines associated with respiratory virus infection illness outcome. However, few studies have included comprehensive cytokine panels, longitudinal analyses, and/or simultaneous assessment across the severity spectrum. This, coupled with subjective definitions of cytokine storm syndrome (CSS), have contributed to inconsistent findings of cytokine signatures, particularly with COVID severity. Here, we measured 38 plasma cytokines and compared profiles in healthy, SARS-CoV-2 infected, and multisystem inflammatory syndrome in children (MIS-C) patients (n = 169). Infected patients spanned the severity spectrum and were classified as Asymptomatic, Mild, Moderate or Severe. Our results showed acute cytokine profiles and longitudinal dynamics of IL1Ra, IL10, MIP1b, and IP10 can differentiate COVID severity groups. Only 4% of acutely infected patients exhibited hypercytokinemia. Of these subjects, 3 were Mild, 3 Moderate, and 1 Severe, highlighting the lack of association between CSS and COVID severity. Additionally, we identified IL1Ra and TNFa as potential biomarkers for patients at high risk for long COVID. Lastly, we compare hypercytokinemia profiles across COVID and influenza patients and show distinct elevated cytokine signatures, wherein influenza induces the most elevated cytokine profile. Together, these results identify key analytes that, if obtained at early time points, can predict COVID illness outcome and/or risk of complications, and provide novel insight for improving the conceptual framework of hypercytokinemia, wherein CSS is a subgroup that requires concomitant severe clinical manifestations, and including a list of cytokines that can distinguish between subtypes of hypercytokinemia.

immunology↗

The Promise and Pitfalls of Prophages

Phages dominate every ecosystem on the planet. While virulent phages sculpt the microbiome by killing their bacterial hosts, temperate phages provide unique growth advantages to their hosts through lysogenic conversion. Many prophages benefit their host, and prophages are responsible for genotypic and phenotypic differences that separate individual microbial strains. However, the microbes also endure a cost to maintain those phages: additional DNA to replicate and proteins to transcribe and translate. We have never quantified those benefits and costs. Here, we analysed over two and a half million prophages from over half a million bacterial genome assemblies. Analysis of the whole dataset and a representative subset of taxonomically diverse bacterial genomes demonstrated that the normalised prophage density was uniform across all bacterial genomes above 2 Mbp. We identified a constant carrying capacity of phage DNA per bacterial DNA. We estimated that each prophage provides cellular services equivalent to approximately 2.4 % of the cells energy or 0.9 ATP per bp per hour. We demonstrate analytical, taxonomic, geographic, and temporal disparities in identifying prophages in bacterial genomes that provide novel targets for identifying new phages. We anticipate that the benefits bacteria accrue from the presence of prophages balance the energetics involved in supporting prophages. Furthermore, our data will provide a new framework for identifying phages in environmental datasets, diverse bacterial phyla, and from different locations.

bioinformatics↗

Programmed ribosomal frameshifts, and how to find them

One of the stranger phenomena that can occur during gene translation is where, as a ribosome reads along the mRNA, various cellular and molecular properties contribute to stalling the ribosome on a slippery sequence, shifting the ribosome into one of the other two alternate reading frames. The alternate frame has different codons, so different amino acids are added to the peptide chain, but more importantly, the original stop codon is no longer in-frame, so the ribosome can bypass the stop codon and continue to translate the codons past it. This produces a longer version of the protein, a fusion of the original in-frame amino acids, followed by all the alternate frame amino acids. There is currently no automated software to predict the occurrence of these programmed ribosomal frameshifts (PRF), and they are currently only identified by manual curation. Here we present the first machine-learning based method to detect and predict the presence of PRFs in all types of coding genes and taxa with an accuracy exceding 90%.

bioinformatics↗

Novel crAssphage isolates exhibit conserved gene order and purifying selection of the host specificity protein

Bacteroides, the prominent bacteria in the human gut, play a crucial role in degrading complex polysaccharides. Their abundance is influenced by phages belonging to the Crassvirales order. Despite identifying over 600 Crassvirales genomes computationally, only few have been successfully isolated. Continued efforts in isolation of more Crassvirales genomes can provide insights into phage-host-evolution and infection mechanisms. We focused on wastewater samples, as potential sources of phages infecting various Bacteroides hosts. Sequencing, assembly, and characterization of isolated phages revealed 14 complete genomes belonging to three novel Crassvirales species infecting Bacteroides cellulosilyticus WH2. These species, Kehishuvirus sp. tikkala strain Bc01, Kolpuevirus sp. frurule strain Bc03, and Rudgehvirus jaberico strain Bc11, spanned two families, and three genera, displaying a broad range of virion productions. Upon testing all successfully cultured Crassvirales species and their respective bacterial hosts, we discovered that they do not exhibit co-evolutionary patterns with their bacterial hosts. Furthermore, we observed variations in gene similarity, with greater shared similarity observed within genera. However, despite belonging to different genera, the three novel species shared a unique structural gene that encodes the tail spike protein. When investigating the relationship between this gene and host interaction, we discovered evidence of purifying selection, indicating its functional importance. Moreover, our analysis demonstrated that this tail spike protein binds to the TonB-dependent receptors present on the bacterial host surface. Combining these observations, our findings provide insights into phage-host interactions and present three Crassvirales species as an ideal system for controlled infectivity experiments on one of the most dominant members of the human enteric virome. Impact statementBacteriophages play a crucial role in shaping microbial communities within the human gut. Among the most dominant bacteriophages in the human gut microbiome are Crassvirales phages, which infect Bacteroides. Despite being widely distributed, only a few Crassvirales genomes have been isolated, leading to a limited understanding of their biology, ecology, and evolution. This study isolated and characterized three novel Crassvirales genomes belonging to two different families, and three genera, but infecting one bacterial host, Bacteroides cellulosilyticus WH2. Notably, the observation confirmed the phages are not co-evolving with their bacterial hosts, rather have a shared ability to exploit similar features in their bacterial host. Additionally, the identification of a critical viral protein undergoing purifying selection and interacting with the bacterial receptors opens doors to targeted therapies against bacterial infections. Given Bacteroides role in polysaccharide degradation in the human gut, our findings advance our understanding of the phage-host interactions and could have important implications for the development of phage-based therapies. These discoveries may hold implications for improving gut health and metabolism to support overall well-being. Data summaryThe genomes used in this research are available on Sequence Read Archive (SRA) within the project, PRJNA737576. Bacteroides cellulosilyticus WH2, Kehishuvirus sp. tikkala strain Bc01, Kolpuevirus sp. frurule strain Bc03, and Rudgehvirus jaberico strain Bc11 are all available on GenBank with accessions NZ_CP072251.1 (B. cellulosilyticus WH2), QQ198717 (Bc01), QQ198718 (Bc03), and QQ198719 (Bc11), and we are working on making the strains available through ATCC. The 3D protein structures for the three Crassvirales genomes are available to download at doi.org/10.25451/flinders.21946034.

bioinformatics↗

Philympics 2021: Prophage Predictions Perplex Programs

Most bacterial genomes contain integrated bacteriophages--prophages--in various states of decay. Many are active and able to excise from the genome and replicate, while others are cryptic prophages, remnants of their former selves. Over the last two decades, many computational tools have been developed to identify the prophage components of bacterial genomes, and it is a particularly active area for the application of machine learning approaches. However, progress is hindered and comparisons thwarted because there are no manually curated bacterial genomes that can be used to test new prophage prediction algorithms. Here, we present a library of gold-standard bacterial genome annotations that include manually curated prophage annotations, and a computational framework to compare the predictions from different algorithms. We use this suite to compare all extant stand-alone prophage prediction algorithms to identify their strengths and weaknesses. We provide a FAIR dataset for prophage identification, and demonstrate the accuracy, precision, recall, and f1 score from the analysis of seven different algorithms for the prediction of prophages. We discuss caveats and concerns in this analysis and how those concerns may be mitigated.

bioinformatics↗

MultiPhATE2: Code for Functional Annotation and Comparison of Bacteriophage Genomes

To address the need for improved tools for annotation and comparative genomics of bacteriophage genomes, we developed multiPhATE2. As an extension of the multiPhATE code, multiPhATE2 performs gene finding and functional sequence annotation of predicted gene and protein sequences, and additional search algorithms and databases extend the search space of the original functional annotation subsystem. MultiPhATE2 includes comparative genomics codes for gene matching among sets of input bacteriophage genomes, and scales well to large input data sets with the incorporation of multiprocessing in the functional annotation and comparative genomics subsystems. MultiPhATE2 was implemented in Python 3.7 and runs as a command-line code under Linux or MAC-OS. MultiPhATE2 is freely available under an open-source GPL-3 license at https://github.com/carolzhou/multiPhATE2. Instructions for acquiring the databases and third party codes used by multiPhATE2 are found in the README file included with the distribution. Users may report bugs by submitting issues to the project GitHub repository webpage. Contact: zhou4@llnl.gov or multiphate@gmail.com. Supplementary materials, which demonstrate the outputs of multiPhATE2, are available in a GitHub repository, at https://github.com/carolzhou/multiPhATE2_supplementaryData/.

bioinformatics↗

A Distinct Contractile Injection System Found in a Majority of Adult Human Microbiomes

An imbalance of normal bacterial groups such as Bacteroidales within the human gut is correlated with diseases like obesity. A current grand challenge in the microbiome field is to identify factors produced by normal microbiome bacteria that cause these observed health and disease correlations. While identifying factors like a bacterial injection system could provide a missing explanation for why Bacteroidales correlates with host health, no such factor has been identified to date. The lack of knowledge about these factors is a significant barrier to improving therapies like fecal transplants that promote a healthy microbiome. Here we show that a previously ill-defined Contractile Injection System is carried in the gut microbiome of 99% of individuals from the United States and Europe. This type of Contractile Injection System, we name here Bacteroidales Injection System (BIS), is related to the contractile tails of bacteriophage (viruses of bacteria) and have been described to mediate interactions between bacteria and diverse eukaryotes like amoeba, insects and tubeworms. Our findings that BIS are ubiquitous within adult human microbiomes suggest that they shape host health by mediating interactions between Bacteroidales bacteria and the human host or its microbiome.

microbiology↗

Global phylogeography and ancient evolution of the widespread human gut virus crAssphage

Microbiomes are vast communities of microbes and viruses that populate all natural ecosystems. Viruses have been considered the most variable component of microbiomes, as supported by virome surveys and examples of high genomic mosaicism. However, recent evidence suggests that the human gut virome is remarkably stable compared to other environments. Here we investigate the origin, evolution, and epidemiology of crAssphage, a widespread human gut virus. Through a global collaboratory, we obtained DNA sequences of crAssphage from over one-third of the worlds countries, and showed that its phylogeography is locally clustered within countries, cities, and individuals. We also found colinear crAssphage-like genomes in both Old-World and New-World primates, challenging genomic mosaicism and suggesting that the association of crAssphage with primates may be millions of years old. We conclude that crAssphage is a benign globetrotter virus that may have co-evolved with the human lineage and an integral part of the normal human gut virome.

microbiology↗

THEA: A novel approach to gene identification in phage genomes

MotivationCurrently there are no tools specifically designed for annotating genes in phages. Several tools are available that have been adapted to run on phage genomes, but due to their underlying design they are unable to capture the full complexity of phage genomes. Phages have adapted their genomes to be extremely compact, having adjacent genes that overlap, and genes completely inside of other longer genes. This non-delineated genome structure makes it difficult for gene prediction using the currently available gene annotators. Here we present THEA (The Algorithm), a novel method for gene calling specifically designed for phage genomes. While the compact nature of genes in phages is a problem for current gene annotators, we exploit this property by treating a phage genome as a network of paths: where open reading frames are favorable, and overlaps and gaps are less favorable, but still possible. We represent this network of connections as a weighted graph, and use graph theory to find the optimal path.\n\nResultsWe compare THEA to other gene callers by annotating a set of 2,133 complete phage genomes from GenBank, using THEA and the three most popular gene callers. We found that the four programs agree on 82% of the total predicted genes, with THEA predicting significantly more genes than the other three. We searched for these extra genes in both GenBanks non-redundant protein database and sequence read archive, and found that they are present at levels that suggest that these are functional protein coding genes.\n\nAvailability and ImplementationThe source code and all files can be found at: https://github.com/deprekate/THEA\n\nContactKatelyn McNair: deprekate@gmail.com

bioinformatics↗

Prophage genomics reveals patterns in phage genome organization and replication

Temperate phage genomes are highly variable mosaic collections of genes that infect a bacterial host, integrate into the hosts genome or replicate as low copy number plasmids, and are regulated to switch from the lysogenic to lytic cycles to generate new virions and escape their host. Genomes from most Bacterial phyla contain at least one or more prophages. We updated our PhiSpy algorithm to improve detection of prophages and to provide a web-based framework for PhiSpy. We have used this algorithm to identify 36,488 prophage regions from 11,941 bacterial genomes, including almost 600 prophages with no known homology to any proteins. Transfer RNA genes were abundant in the prophages, many of which alleviate the limits of translation efficiency due to host codon bias and presumably enable phages to surpass the normal capacity of the hosts translation machinery. We identified integrase genes in 15,765 prophages (43% of the prophages). The integrase was routinely located at either end of the integrated phage genome, and was used to orient and align prophage genomes to reveal their underlying organization. The conserved genome alignments of phages recapitulate early, middle, and late gene order in transcriptional control of phage genes, and demonstrate that gene order, presumably selected by transcription timing and/or coordination among functional modules has been stably conserved throughout phage evolution.

biochemistry↗