Biology subjects

Brown, S. M.

Publications and source records attributed to Brown, S. M..

13 recordsLinked to original sources

bioRxiv2026

The genetically-encoded amino acids distribute non-randomly within a functionally-relevant chemical space

The standard set of 20 genetically-encoded amino acids (C20) exhibits a statistically non-random distribution in primarily two structurally-relevant physicochemical properties: hydrophobicity and molecular volume, and to a lesser extent charge. It remains an open question, however, whether evolutionary pressures similarly optimized the same alphabet for the distribution of functionally-relevant properties, such as reactivity. In this study, we used semi-empirical quantum chemistry simulations to calculate the highest occupied molecular orbital and lowest unoccupied molecular orbital (HOMO-LUMO) gaps for 84 xeno amino acids and constructed 10 million random 20-mer amino acid alphabets to determine where C20 fit amongst this background. The HOMO-LUMO gap measurements demonstrated that C20, similar to hydrophobicity and volume, also exhibits a non-random distribution. However, unlike hydrophobicity and volume, this distribution is non-random across an unevenly broad range. The results expand upon previous theory and suggest HOMO-LUMO gap energies as one synthetic biologists may consider when developing novel protein design tools or designing functional xeno amino acid alphabets. HighlightsO_LILifes amino acid alphabet is non-randomly distributed within an expanded computationally-generated chemistry space generated from large-scale quantum chemistry simulations. C_LIO_LIAmino acid alphabet coverage theory applies beyond structurally-relevant physicochemical descriptors to include functionally-relevant properties like reactivity as measured by frontier molecular orbitals C_LIO_LIFindings here provide a theoretical framework to guide the design of novel proteins and development of synthetic amino acid alphabets. C_LI

synthetic biology↗

bioRxiv2026

Artificial intelligence aided design of peptides with custom secondary structure motifs and reduced amino acid alphabets

Proteins are highly diverse functional polymers where the specific sequence of amino acids, selected from a standard genetically-encoded alphabet of twenty (C20), determines the structure and ultimately the function of the resulting folded protein. This standard alphabet has been identified to be non-randomly distributed in physicochemical properties crucial to both structure-formation and function, often referred to as coverage theory. While machine learning models have drastically improved protein structure prediction, success of protein design models lags structure prediction, particularly for custom secondary structure motifs and amino acid alphabets. Here we therefore bridge contemporary biological theory with recent advancements in artificial intelligence (AI) to develop and evaluate a generative AI protein design model, trained on hundreds of thousands of proteins within the RSCB PDB, for custom secondary structure motifs using reduced amino acid alphabets (RAAs). Results indicate an overall success in designing novel proteins with desired secondary structure motifs for a broad range of amino acid alphabets and complexity of designs. Interestingly, this tool often captures the full three-dimensional tertiary structure of a target protein despite training only on physicochemical sequence space and secondary structure information. The development of this model advances research across multiple disciplines, from general scientific AI architecture development to protein design for biotechnology, astrobiology, and early-Earth evolutionary biology.

bioinformatics↗

bioRxiv2026

Xeno amino acid alphabets form peptides with familiar secondary structure

Summary paragraphThe central dogma of molecular biology describes how genetic information stored in nucleic acids guides the formation of structured proteins from a single molecular alphabet of twenty amino acids (C20)1,2. The extent to which C20 is uniquely capable of forming structural polymers remains a fundamental open question. Here we demonstrate that peptides built from other, "xeno" amino acid alphabets can adopt protein-like secondary structural motifs. Having designed two different xeno alphabets, with them we constructed both combinatorial random sequence libraries and specific, designed 25-mer sequences. We report sequence-dependent structural motifs that result according to circular dichroism, infrared spectroscopy and nuclear magnetic resonance interpreted by molecular dynamics simulations, supported by extensive quantum mechanical calculations. This evidence, including a solution-phase NMR-resolved helical motif, demonstrates that the potential for amino acids to form structure bearing sequences is not unique to lifes alphabet, and thereby reveals a previously unexplored sequence-structure space. Results inform the search for extraterrestrial life, lay foundations for incorporating novel synthetic functional groups and heteroatoms into structure-bearing alphabets, and provide the first truly independent data with which to test and improve all that has been learned about protein folding from the study of lifes 20 side chains.

biochemistry↗

bioRxiv2025

Prebiotically Plausible Peptides can Self-assemble into β-rich Nanostructures

Peptides can self-assemble into diverse morphologies in a programmable manner and hence are privileged building blocks used widely in nanotechnology. Most reported peptide nanostructures consist of one (or a few) defined sequence(s), as self-similarity is presumed to be essential for promoting assembly. While oligomerisation is seen as an important feature of the earliest functional polymers during the origin of life, prebiotic peptides were likely short, statistical, and non-templated - traits that seem incommensurate with robust self-assembly. Here we show that random 25-mer peptides can efficiently and spontaneously form highly thermostable, soluble assemblies rich with beta-sheets. Notably, these nanostructures only emerge when random peptides are constructed with an early alphabet, consisting of the 10 canonical amino acids that were also prebiotically abundant - but not other alphabets tested. Hence, our findings show that peptide self-assembly does not require purity, and in fact compositional complexity is adaptive for preventing formation of insoluble structures. Altogether, this study showcases that unevolved sequences of prebiotically-abundant amino acids can readily produce foldable self-assembling polymers, thereby providing a potential steppingstone toward the first proteins, prior to the onset of purifying selection.

biochemistry↗

bioRxiv2025

Glucocorticoid and Mineralocorticoid Receptors Jointly Promote Vascular Development in Kidney Organoids

To examine the co-development of vasculature and renal epithelial tissue, we employed a human pluripotent stem cell-derived kidney organoid system. We found that cooperative signaling through the glucocorticoid receptor and mineralocorticoid receptor via hydrocortisone enabled rich endothelial cell differentiation and vessel formation. Bulk RNA sequencing analysis revealed that hydrocortisone perturbs an angiogenic transcriptional program early in development and promotes instead a pro-endothelial survival transcriptional program, with upregulation of angiopoietin 1 at both the mRNA and protein level. Additionally, we saw that hydrocortisone does not seem to significantly affect gene expression of canonical nephrogenic genes compared to our controls, suggesting its effect is largely restricted to endothelial cell differentiation. Our results show that kidney organoids offer a unique platform to study developmental signals that drive endothelial cell differentiation and vessel formation.

developmental biology↗

bioRxiv2022

De novo assembly and annotation of the singing mouse genome

BackgroundDeveloping genomic resources for a diverse range of species is an important step towards understanding the mechanisms underlying complex traits.Specifically, organisms that exhibit unique, accessible phenotypes-of-interests, allow researchers to address questions that may be ill-suited to traditional model organisms. We sequenced the genome and transcriptome of Alstons singing mouse (Scotinomys teguina), an emerging model for social cognition and vocal communication. In addition to producing advertisement songs used for mate attraction and male-male competition, these rodents are diurnal, live at high-altitudes, and are obligate insectivores, providing opportunities to explore diverse physiological, ecological, and evolutionary questions. ResultsUsing PromethION, Illumina, and PacBio sequencing, we produced an annotated genome and transcriptome, which were validated using gene expression and functional enrichment analyses. To assess the usefulness of our assemblies, we performed single nuclei sequencing on cells of the orofacial motor cortex, a brain region implicated in song coordination, identifying 12 cell types. ConclusionsThese resources will provide the opportunity to identify the molecular basis of complex traits in singing mice as well as to contribute data that can be used for large-scale comparative analyses.

genomics↗

bioRxiv2022

Multi-omic analysis of the cardiac cellulome defines a vascular contribution to cardiac diastolic dysfunction in obese female mice

Coronary microvascular dysfunction (CMD) is associated with cardiac dysfunction and predictive of cardiac mortality in obesity, especially in females. Emerging evidence suggests development of heart failure with preserved ejection fraction in females with CMD and that mineralocorticoid receptor (MR) antagonism may be more efficacious in obese female, versus male, HFpEF patients. Accordingly, we examined the hypothesis that smooth muscle cell (SMC)-specific MR deletion prevents obesity-associated coronary and cardiac diastolic dysfunction in females. Obesity was induced in female mice via western diet (WD) feeding alongside littermates fed standard diet. Initial studies revealed that global MR blockade with spironolactone prevented impaired coronary vasodilation and diastolic dysfunction in obese females. Importantly, specific deletion of SMC-MR similarly prevented obesity-associated coronary and cardiac dysfunction. Cardiac gene expression profiling suggested reduced cardiac inflammation in WD-fed mice with SMC-MR deletion independent of blood pressure, aortic stiffening, and cardiac hypertrophy. Further mechanistic studies utilizing single-cell RNA sequencing of non-cardiomyocyte cell populations revealed novel impacts of SMC-MR deletion on the cardiac cellulome in obese mice. Specifically, WD feeding induced inflammatory gene signatures in multiple non-myocyte populations (B/T cells, macrophages, and endothelium), independent of cardiac fibrosis, that was prevented by SMC-MR deletion. Further, SMC-MR deletion induced a basal reduction in cardiac mast cells and prevented WD-induced cardiac pro-inflammatory chemokine expression and leukocyte recruitment. These data reveal a central role for SMC-MR signaling in obesity-associated coronary and cardiac dysfunction thus supporting the emerging paradigm of a vascular origin of cardiac dysfunction in obesity.

physiology↗

bioRxiv2021

Stem cell-derived macrophages as a new platform for studying host-pathogen interactions in livestock

Infectious diseases of farmed and wild animals pose a recurrent threat to food security and human health. The macrophage, a key component of the innate immune system, is the first line of defence against many infectious agents and plays a major role in shaping the adaptive immune response. However, this phagocyte is a target and host for many pathogens. Understanding the molecular basis of interactions between macrophages and pathogens is therefore crucial for the development of effective strategies to combat important infectious diseases. We explored how pluripotent stem cells (PSCs) can provide a limitless in vitro supply of genetically and experimentally tractable macrophages from livestock. Porcine and bovine PSC-derived macrophages (PSCdMs) exhibited molecular and functional characteristics of ex vivo primary macrophages. Pig PSCdMs were productively infected by Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) and African Swine Fever Virus (ASFV), two of the most economically important and devastating viruses in pig farming. Moreover, Pig PSCdMs were readily amenable to genetic modification by CRISPR/Cas9 gene editing applied in parental stem cells, or directly by lentiviral vector transduction. PSCs and differentiated derivatives therefore provide a useful and ethical experimental platform to investigate the genetic and molecular basis of host-pathogen interactions in livestock.

immunology↗

bioRxiv2021

Defining the pig microglial transcriptome reveals their core signature, regional heterogeneity, and similarity with humans

Microglia play key roles in brain homeostasis as well as responses to neurodegeneration and neuroinflammatory processes caused by physical disease and psychosocial stress. The pig is a physiologically-relevant model species for studying human neurological disorders, many of which are associated with microglial dysfunction. Furthermore, pigs are an important agricultural species, and there is a need to understand how microglial function affects their welfare. As a basis for improved understanding to enhance biomedical and agricultural research, we sought to characterise pig microglial identity at genome-wide scale and conduct inter-species comparisons. We isolated pig hippocampal tissue and microglia from frontal cortex, hippocampus and cerebellum, as well as alveolar macrophages from the lungs and conducted RNA-sequencing (RNAseq). By comparing the transcriptomic profiles between microglia, macrophages, and hippocampal tissue, we derived a set of 365 highly-enriched genes defining the porcine core microglial signature. We found brain regional heterogeneity based on 215 genes showing significant (adjusted p<0.01) regional variations and that cerebellar microglia were most distinct. We compared normalized gene expression for microglia from human, mice and pigs using microglia signature gene lists derived from each species and demonstrated that a core microglial marker gene signature is conserved across species, but that species-specific expression subsets also exist. Importantly, pig and human microglia shared greater similarity than pig and murine microglia. Our data provide a valuable resource defining the pig microglial transcriptome signature that highlights pigs as a useful large animal species bridging between rodents and humans in which to study the role of microglia during homeostasis and disease. Main Points- Defined a pig microglial transcriptome signature comprising 365 genes. - Demonstrated regional variance in the pig microglial transcriptome across the brain. - Revealed greater similarity between pig and human microglia than mouse.

bioinformatics↗

bioRxiv2018

Type 1 Diabetes: an Association Between Autoimmunity the Dynamics of Gut Amyloid-producing E. coli and Their Phages

The etiopathogenesis of type 1 diabetes (T1D), a common autoimmune disorder, is not completely understood. Recent studies suggested the gut microbiome plays a role in T1D. We have used public longitudinal microbiome data from T1D patients to analyze amyloid-producing bacterial composition and found a significant association between initially high amyloid-producing Escherichia coli abundance, subsequent E. coli depletion prior to seroconversion, and T1D development. In children who presented seroconversion or developed T1D, we observed an increase in the E. coli phage/E. coli ratio prior to E. coli depletion, suggesting that the decrease in E. coli was due to prophage activation. Evaluation of the role of phages in amyloid release from E. coli biofilms in vitro suggested an indirect role of the bacterial phages in the modulation of host immunity.\n\nThis study for the first time suggests that amyloid-producing E. coli, their phages, and bacteria-derived amyloid might be involved in pro-diabetic pathway activation in children at risk for T1D.

microbiology↗

bioRxiv2018

Environmentally enriched pigs have transcriptional profiles consistent with neuroprotective effects and microglial depletion

Environmental enrichment (EE) is widely used to study the effects of external factors on brain development, function and health in rodent models, but very little is known of the effects of EE on the brain in a large animal model such as the pig. Twenty-four young pigs (aged 5 weeks at start of study, 1:1 male: female ratio) were housed in environmentally enriched (EE) pens and provided with additional enrichment stimulation (a bag filled with straw) once daily. Litter, weight and sex matched controls n= (24) were housed in barren (B) conditions. Behaviour was recorded on alternate days from study day 10. After 21 days, RNA-sequencing of the frontal cortex of male piglets culled one hour after the enrichment stimulation, but not those at 4 hours after stimulation, showed upregulation of genes involved in neuronal activity and synaptic plasticity in the EE compared to the B condition. This result is mirrored in the behavioural response to the stimulation which showed a peak in activity around the 1 hour time-point. By contrast, EE piglets displayed a signature consistent with a relative decrease in microglial activity compared to those in the B condition. These results confirm those from rodents, suggesting that EE may also confer neuronal health benefits in large mammal models, through a potential relative reduction in neuroinflammatory process and increase in neuroprotection driven by an enrichment-induced increase in behavioural activity.

molecular biology↗

bioRxiv2017

HPViewer: Sensitive and specific genotyping of human papillomavirus in metagenomic DNA

BackgroundShotgun DNA sequencing provides sensitive detection of all 182 HPV types in tissue and body fluid. However, existing computational methods either produce false positives misidentifying HPV types due to shared sequences among HPV, human, and prokaryotes, or produce false negative since they identify HPV by assembled contigs requiring large abundant of HPV reads.\n\nResultsWe show that HPV shares extensive simple repeats with human and prokaryotes and homologous sequences among different HPV types. The shared sequences caused errors in HPV genotyping and the repeats of human origin caused false positives in HPVDetector. Programs, such as VirusTAP and Vipie, which require de novo assembly of shotgun reads into contigs, eliminated false positives at a cost of substantial reduction in sensitivity. Here, we designed HPViewer with two custom HPV reference databases masking simple repeats and homology sequences respectively and one homology distance matrix to hybridize these two databases. It directly identified HPV from short DNA reads rather than assembled contigs. Using 100,100 simulated samples, we revealed that HPViewer was robust for samples containing either high or low number of HPV reads. Using 12 shotgun sequencing samples from respiratory papillomatosis, HPViewer was equal to VirusTAP, and Vipie and better than HPVDetector with the respect to specificity and was the most sensitive method in the detection of HPV types 6 and 11. We demonstrated that contigs-based approaches had disadvantages of detection of HPV. In 1,573 sets of metagenomic data from 18 human body sites, HPViewer identified 104 types of HPV in a body-site associated pattern and 89 types of HPV co-occurring in one sample with other types of HPV at least once.\n\nConclusionsWe demonstrated HPViewer was sensitive and specific for HPV detection in metagenomic data. It was also suggested that masking shared sequences is an effective approach to avoid false positive detection and identifying HPV from short metagenomic reads is more sensitive than assembled contigs. The innovative homology distance matrix connecting two HPV databases, repeat-mask and homology-mask, optimized the balance of sensitivity and specificity. HPViewer can be accessed at https://github.com/yuhanH/HPViewer/.

bioinformatics↗

bioRxiv2017

Fast functional annotation of metagenomic shotgun data by DNA alignment to a microbial gene catalog

BackgroundMetagenomic shotgun sequencing is becoming increasingly popular to study microbes associated with the human body and in environmental samples. A key goal of shotgun metagenomic sequencing is to identify gene functions and metabolic pathways that differ between samples or conditions. However, current methods to identify function in the large number of reads in a high-throughput sequence data file rely on the computationally intensive and low stringency approach of mapping each read to a generic database of proteins or reference microbial genomes.\n\nResultsWe have developed an alternative analysis approach for shotgun metagenomic sequence data utilizing Bowtie2 DNA-DNA alignment of the reads to a database of well annotated genes compiled from human microbiome data. This method is rapid, and provides high stringency matches (>90% DNA sequence identity) of shotgun metagenomics reads to genes with annotated functions. We demonstrate the use of this method with synthetic data, Human Microbiome Project shotgun metagenomic data sets, and data from a study of liver disease. Differentially abundant KEGG gene functions can be detected in these experiments.\n\nConclusionsFunctional annotation of metagenomic shotgun sequence reads can be accomplished by rapid DNA-DNA matching to a custom database of microbial sequences using the Bowtie2 sequence alignment tool. This method can be used for a variety of microbiome studies and allows functional analysis which is otherwise computationally demanding. This rapid annotation method is freely available as a Galaxy workflow within a Docker image.

bioinformatics↗