Biology subjects

Wade, J.

Publications and source records attributed to Wade, J..

18 recordsLinked to original sources

bioRxiv2026

Non-random brain connectome wiring enables robust and efficient neural network function under high sparsity

The connectivity of brain networks is extremely sparse due to metabolic, physical and spatial constraints. Although wiring sparsity can confer computational advantages for biological and artificial neural networks, sparse networks require fine parameter tuning and exhibit strong sensitivity to perturbations. How brains achieve their efficiency and robustness is unclear. Here we addressed this by analysing the dynamical properties of Echo State Networks with wiring based on the Drosophila melanogaster fruit fly connectome, compared with sparsity-matched random-wiring networks. We evaluated these networks on a set of eight cognitive tasks, and found that connectome-based neural networks (CoNNs) typically showed narrowly distributed task engagement across their neurons. The importance of a neuron for task performance correlated with its node degree, local clustering, and selfrecurrency, and these correlations were stronger in CoNNs than in random networks. CoNNs were more robust to neuronal loss, retaining their task performance and beneficial dynamical properties such as criticality and spectral radius better than random networks. Similarly, CoNNs were more robust to hyperparameter variations in both input and recurrent weight scaling. Using theoretical arguments and numerical simulations, we show that excess CoNN node self-recurrency is sufficient to explain this enhanced robustness. Overall, these results identify non-random features of connectome wiring that allow brains to reconcile extreme sparsity with reliable computation. SignificanceBrain networks support robust computation even though they operate under extreme wiring sparsity due to metabolic and spatial constraints. While sparse networks typically require fine-tuning and are sensitive to perturbations, we show that biological connectomes support specialised, efficient task engagement and remain robust to neuron loss and parameter variation. We identify excess neuronal selfrecurrency as a key structural feature underlying this stability. These results reveal how non-random connectivity stabilises computation in extremely sparse networks, providing principles for understanding brain function and designing robust, efficient artificial neural systems.

neuroscience↗

bioRxiv2025

Phase separation of mycobacterial Rho factor is associated with acid stress

Rho is a bacterial transcription termination factor that contains additional regions in some species, including many mycobacteria. These additional regions are compositionally biased and are predicted to be intrinsically disordered and associated with Liquid-Liquid Phase Separation (LLPS). However, LLPS has only been experimentally demonstrated for Rho from Bacteroides thetaiotaomicron. Here, we extend a prior bioinformatic analysis of Rho from mycobacterial species, where Rho has additional regions that differ from Rho in B. thetaiotaomicron. We show that Mycolicibacterium smegmatis Rho forms in vitro and in vivo condensates by LLPS, and that LLPS depends upon the additional regions. In vitro, droplet formation for Rho from four mycobacterial species was modulated by the presence of RNA and was observed for the intrinsically disordered regions alone, suggesting that these regions are sufficient for droplet formation. Moreover, Rho phase separation in living M. smegmatis cells occurs during acid stress and may impact cell fitness. This phenotype is due to Rhos additional regions, since engineered mycobacterial Rho lacking the additional regions does not undergo LLPS. In summary, our results indicate that LLPS is a widespread mechanism in which mycobacterial Rho assembles into condensates, possibly terminating the transcription of different genes, which allows tolerance to stress conditions.

microbiology↗

bioRxiv2025

Cell-type specific iron content regulation revealed by single-cell iron quantification

Iron is crucial for cellular metabolism and cell growth. Nevertheless, in humans, both iron deficiency and disorders of iron overload are widespread. How cellular iron content varies depending upon iron availability, and how this influences cell function is poorly characterised. We developed a method to quantify metals in hundreds of cells per minute via single-cell inductively-coupled plasma mass spectrometry (sc-ICP-MS), and used this to explore iron usage by immune cells. Activated murine T-cells exposed to a 625-fold titration of extracellular iron maintained close homeostatic control, with iron content varying by [~]20%. However, these variations strongly correlated with activation characteristics and proliferation. Running sc-ICP-MS downstream of flow cytometric sorting showed that murine T-cells and B-cells ex vivo exhibit similar mean and heterogeneity of cellular iron while splenic macrophages contain twice as much iron and more heterogeneous iron content. Finally, activated human B-cells contain [~]10-fold more iron per cell than murine B-cells. We suggest that mechanisms of iron homeostasis impart particular ranges or set-points of iron content to different cell types and activation states, and that small changes in iron content have large effects on cell behaviour. Our methodological advance and consequent findings suggest new approaches to studying the biology of metals.

cell biology↗

bioRxiv2024

Rapid and precise quantification of lymphocyte iron content by single cell inductively coupled plasma mass spectrometry

Metals facilitate catalysis during cellular metabolism, but heterogeneity of metal content at single-cell level within and between cell populations is poorly characterized. This is important because deficiencies of biometals, for example iron, are enormously prevalent worldwide. Here we quantify metal content of single-cells using inductively-coupled plasma mass spectrometry. To develop the method, we used rhodium and iridium-intercalated Jurkat cells, obtaining >0.96% r2 cross-analytical correlation with mass cytometry. We quantified iron and calcium mass/cell for murine T-lymphocytes with 3% and 8% 2-sigma intra-precision, respectively, when assessing thousands of cells/minute. T-lymphocytes exposed to a 625-fold difference in extracellular iron concentrations maintained close iron homeostatic control, varying [~]20% in iron content. Nevertheless, this relatively small variation strongly correlated with changes in cellular activation characteristics measured by flow cytometry. We also assessed human B-cell iron content, which was [~]10-fold higher than murine T-lymphocytes. Overall, we demonstrate rapid iron quantification at single-cell level in different cell types and relate cellular iron content to cell function. TeaserPrecise and rapid iron metallomics of lymphocytes by single cell ICP-MS is a powerful approach for accessing signatures of immunological status.

immunology↗

bioRxiv2024

A Cryptic Prophage Transcription Factor Drives Phenotypic Changes via Host Gene Regulation

Cryptic prophages (CPs) are elements of bacterial genomes acquired from bacteriophage that infect the host cell and ultimately become stably integrated within the host genome. While some proteins encoded by CPs can modulate host phenotypes, the potential for Transcription Factors (TFs) encoded by CPs to impact host physiology by regulating host genes has not been thoroughly investigated. In this work, we report hundreds of host genes regulated by DicC, a DNA-binding TF encoded in the Qin prophage of Esherichia coli. We identified host-encoded regulatory targets of DicC that could be linked to known phenotypes of its induction. We also demonstrate that a DicC-induced growth defect is largely independent of other Qin prophage genes. Our data suggest a greater role for cryptic prophage TFs in controlling bacterial host gene expression than previously appreciated.

microbiology↗

bioRxiv2024

Diversification of the Rho transcription termination factor in bacteria

Correct termination of transcription is essential for gene expression. In bacteria, factor-dependent termination relies on the Rho factor, that classically has three conserved domains. Some bacteria also have a functional insertion region. However, the variation in Rho structure among bacteria has not been analyzed in detail. This study determines the distribution, sequence conservation, and predicted features of Rho factors with diverse domain architectures by analyzing 2,730 bacterial genomes. About half (49.8%) of the species analyzed have the typical Escherichia coli like Rho while most of the other species (39.8%) have diverse, atypical forms of Rho. Besides conservation of the main domains, we describe a duplicated RNA-binding domain present in specific species and novel variations in the bicyclomycin binding pocket. The additional regions observed in Rho proteins exhibit remarkable diversity. Commonly, however, they have exceptional amino acid compositions and are predicted to be intrinsically disordered, to undergo phase separation, or have prion-like behavior. Phase separation has recently been shown to play roles in Rho function and bacterial fitness during harsh conditions in one species and this study suggests a more widespread role. In conclusion, diverse atypical Rho factors are broadly distributed among bacteria, suggesting additional cellular roles.

molecular biology↗

bioRxiv2024

Predictive Biophysical Neural Network Modeling of a Compendium of in vivo Transcription Factor DNA Binding Profiles for Escherichia coli

The DNA binding of most Escherichia coli Transcription Factors (TFs) has not been comprehensively mapped, and few have models that can quantitatively predict binding affinity. We report the global mapping of in vivo DNA binding for 139 E. coli TFs using ChIP-Seq. We used these data to train BoltzNet, a novel neural network that predicts TF binding energy from DNA sequence. BoltzNet mirrors a quantitative biophysical model and provides directly interpretable predictions genome-wide at nucleotide resolution. We used BoltzNet to quantitatively design novel binding sites, which we validated with biophysical experiments on purified protein. We have generated models for 125 TFs that provide insight into global features of TF binding, including clustering of sites, the role of accessory bases, the relevance of weak sites, and the background affinity of the genome. Our paper provides new paradigms for studying TF-DNA binding and for the development of biophysically motivated neural networks.

bioinformatics↗

bioRxiv2023

A Comparative Study of Protein Structure Prediction Tools for Challenging Targets: Snake Venom Toxins

Protein structure determination is a critical aspect of biological research, enabling us to understand protein function and potential applications. Recent advances in deep learning and artificial intelligence have led to the development of several protein structure prediction tools, such as AlphaFold2 and ColabFold. However, their performance has primarily been evaluated on well-characterised proteins, and comparisons using proteins with poor reference templates are lacking. In this study, we evaluated three modelling tools on their prediction of over 1000 snake venom toxin structures with no reference templates. Our findings show that AlphaFold2 (AF2) performed the best across all assessed parameters. We also observed that ColabFold (CF) only scored slightly worse than AF2, while being computationally less intensive. All tools struggled with regions of intrinsic disorder, such as loops and propeptide regions, and performed well in predicting the structure of functional domains. Overall, our study highlights the importance of exercising caution when working with proteins that have poor reference templates, are large, and contain flexible regions. Nonetheless, leveraging computational structure prediction tools can provide valuable insights into the modelling of protein interactions with different targets and reveal potential binding sites, active sites, and conformational changes, as well as into the design of potential molecular binders for reagent, diagnostic, or therapeutic purposes. StatementRecent advances in machine learning have led to the development of new protein structure prediction tools. However, these tools have mainly been tested on well-known proteins and their performance on proteins without known templates is unclear. This study evaluated the performance of three tools on over 1000 snake venom toxins. We found that while caution is required when studying poorly characterised proteins, these tools offer valuable opportunities to understand protein function and applications.

bioinformatics↗

bioRxiv2023

The small mycobacterial ribosomal protein, bS22, modulates aminoglycoside accessibility to its 16S rRNA helix-44 binding site

Treatment of tuberculosis continues to be challenging due to the widespread latent form of the disease and the emergence of antibiotic-resistant strains of the pathogen, Mycobacterium tuberculosis. Bacterial ribosomes are a common and effective target for antibiotics. Several second line anti-tuberculosis drugs, e.g. kanamycin, amikacin, and capreomycin, target ribosomal RNA to inhibit protein synthesis. However, M. tuberculosis can acquire resistance to these drugs, emphasizing the need to identify new drug targets. Previous cryo-EM structures of the M. tuberculosis and M. smegmatis ribosomes identified two novel ribosomal proteins, bS22 and bL37, in the vicinity of two crucial drug-binding sites: the mRNA-decoding center on the small (30S), and the peptidyl-transferase center on the large (50S) ribosomal subunits, respectively. The functional significance of these two small proteins is unknown. In this study, we observe that an M. smegmatis strain lacking the bs22 gene shows enhanced susceptibility to kanamycin compared to the wild-type strain. Cryo-EM structures of the ribosomes lacking bS22 in the presence and absence of kanamycin suggest a direct role of bS22 in modulating the 16S rRNA kanamycin-binding site. Our structures suggest that amino-acid residue Lys-16 of bS22 interacts directly with the phosphate backbone of helix 44 of 16S rRNA to influence the micro-configuration of the kanamycin-binding pocket. Our analysis shows that similar interactions occur between eukaryotic homologues of bS22, and their corresponding rRNAs, pointing to a common mechanism of aminoglycoside resistance in higher organisms.

biochemistry↗

bioRxiv2022

Discovery of a broadly-neutralizing human antibody that can rescue mice challenged with neurotoxin-rich snake venoms

Snakebite envenoming continues to claim many lives across the globe, necessitating the development of improved therapies. To this end, human monoclonal antibodies may possess advantages over current plasma-derived antivenoms by offering superior safety and improved neutralization capacity. However, as new antivenom products may need to be polyvalent, i.e., target multiple different snake species, without dramatically increasing dose or cost of manufacture, such monoclonal antibodies need to be broadly-neutralizing. Here, we report the establishment of a pipeline for the discovery of high affinity broadly-neutralizing human monoclonal antibodies. We further demonstrate its utility by discovering an antibody that can prevent lethality induced by N. kaouthia whole venom at an unprecedented low molar ratio of one antibody per toxin, and which also prolongs survival of mice injected with Dendroaspis polylepis or Ophiophagus hannah whole venoms.

bioengineering↗

bioRxiv2021

In vitro discovery and optimization of a human monoclonal antibody that neutralizes neurotoxicity and lethality of cobra snake venom

The monocled cobra (Naja kaouthia) is one of the most feared snakes in Southeast Asia. It is a highly dangerous species with a potent venom deriving its toxicity predominantly from abundant long-chain -neurotoxins. The only specific treatment for snakebite envenoming is antivenom, which is based on animal-derived polyclonal antibodies. Despite the lifesaving importance of these medicines over the past 120 years, and their ongoing role in combating snakebite disease, major limitations in safety, supply consistency, and efficacy creates a need for a new generation of improved treatments based on modern biotechnological techniques. Here, we describe the initial discovery and subsequent optimization of a recombinant human monoclonal immunoglobin G (IgG) antibody against -cobratoxin using phage display technology. Affinity maturation of the parental antibody by light chain-shuffling resulted in an 8-fold increase in affinity, translating to a significant increase in in vitro neutralization potency and in vivo efficacy. While the parental antibody prolonged survival of mice challenged with purified -cobratoxin, the optimized antibody prevented lethality when incubated with N. kaouthia whole venom prior to intravenous injection. This study is the first to demonstrate neutralization of whole snake venom by a single recombinant monoclonal antibody. Importantly, this suggests that for venoms whose toxicity relies on a single predominant toxin group, such as that of N. kaouthia, as little as one monoclonal antibody may be sufficient to prevent lethality, thus providing a tantalizing prospect of bringing recombinant antivenoms based on human monoclonal or oligoclonal antibodies to the clinic. One Sentence SummaryA recombinant human monoclonal immunoglobulin G antibody, discovered and optimized using in vitro methods, was demonstrated to neutralize the lethal effect of whole venom from the monocled cobra in mice via abrogation of -neurotoxin-mediated neurotoxicity.

molecular biology↗

bioRxiv2020

Characterization of Primed Adaptation in the Escherichia coli type I-E CRISPR-Cas System

CRISPR-Cas systems are bacterial immune systems that target invading nucleic acid. The hallmark of CRISPR-Cas systems is the CRISPR array, a genetic locus that includes short sequences known as "spacers", that are derived from invading nucleic acid. Upon exposure to an invading nucleic acid molecule, bacteria/archaea with functional CRISPR-Cas systems can add new spacers to their CRISPR arrays in a process known as "adaptation". In type I CRISPR-Cas systems, which represent the majority of CRISPR-Cas systems found in nature, adaptation can occur by two mechanisms: naive and primed. Here, we show that, for the archetypal type I-E CRISPR-Cas system from Escherichia coli, primed adaptation occurs at least 1,000 times more efficiently than naive adaptation. By initiating primed adaptation on the E. coli chromosome, we show that spacers can be acquired across distances of >100 kb from the initially targeted site, and we identify multiple factors that influence the efficiency with which sequences are acquired as new spacers. Thus, our data provide insight into the mechanism of primed adaptation. [This paper has been peer reviewed, with Ailong Ke (Cornell University) serving as the editor. Reviews and point-by-point response, and a marked-up version of the edited manuscript are provided as supplementary files.]

microbiology↗

bioRxiv2019

Dissecting psa locus regulation in Yersinia pestis

The pH 6 antigen of Yersinia pestis is a virulence factor that is expressed in response to high temperature (37 {degrees}C) and low pH (6.0). Previous studies have implicated the PsaE and PsaF regulators in the temperature- and pH-dependent regulation of psaA. Here, we show that PsaE levels are themselves controlled by pH and temperature, explaining the regulation of psaA. We identify hundreds of binding sites for PsaE across the Y. pestis genome, with the majority of binding sites located in intergenic regions. However, we detect direct regulation of very few genes by PsaE, suggesting either that most binding sites are non-regulatory, or that they require additional environmental cues. We also identify the precise binding site for PsaE that is required for temperature- and pH-dependent regulation of psaA. Thus, our data reveal the critical function that PsaE plays in regulation of psaA, and suggest that PsaE may have many additional regulatory targets.

microbiology↗

bioRxiv2019

An antibiotic-sensing leader peptide regulates translation and premature Rho-dependent transcription termination of the topAI gene in Escherichia coli

Expression of many bacterial genes is regulated by cis- and trans-acting elements in their 5 upstream regions (URs). Cis-acting regulatory elements in URs include upstream ORFs (uORF), short ORFs that sense translation stress that manifests as ribosomes stalling at specific codons within the uORF. Here, we show that the transcript encoding the Escherichia coli TopAI-YjhQ toxin-antitoxin system is regulated by a uORF that we name "toiL". We propose that in the absence of translation stress, a secondary structure in the UR represses translation of the topAI transcript by occluding the ribosome-binding site. Translation repression of topAI leads to premature Rho-dependent transcription termination within the topAI ORF. At least five different classes of ribosome-targeting antibiotics relieve repression of topAI. Our data suggest that these antibiotics function by stalling ribosomes at different positions within toiL, thereby altering the RNA secondary structure around the topAI ribosome-binding site. Thus, toiL is a multipurpose uORF that can respond to a wide variety of translation stresses.

microbiology↗

bioRxiv2019

Pervasive Translation in Mycobacterium tuberculosis

Most bacterial ORFs are identified by automated prediction algorithms. However, these algorithms often fail to identify ORFs lacking canonical features such as a length of >50 codons or the presence of an upstream Shine-Dalgarno sequence. Here, we use ribosome profiling approaches to identify actively translated ORFs in Mycobacterium tuberculosis. Most of the ORFs we identify have not been previously described, indicating that the M. tuberculosis transcriptome is pervasively translated. The newly described ORFs are predominantly short, with many encoding proteins of [≤]50 amino acids. Codon usage of the newly discovered ORFs suggests that most have not been subject to purifying selection, and hence do not contribute to cell fitness. Nevertheless, we identify 90 new ORFs (median length of 52 codons) that bear the hallmarks of purifying selection. Thus, our data suggest that pervasive translation of short ORFs in Mycobacterium tuberculosis serves as a rich source for the evolution of new functional proteins.

microbiology↗

bioRxiv2017

The evolutionary impact of Intragenic FliA Promoters in Proteobacteria

Recent work has revealed that large numbers of promoters in bacteria are located inside genes. In contrast, almost all studies of transcription have focused on promoters upstream of genes. Bacterial promoters are recognized by Sigma factors that associate with initiating RNA polymerase. In Escherichia coli, one Sigma factor recognizes the majority of promoters, and six \"alternative\" Sigma factors recognize specific subsets of promoters. One of these alternative Sigma factors, FliA ({sigma}28), recognizes promoters upstream of many flagellar genes. We previously showed that most E. coli FliA binding sites are located inside genes. However, it was unclear whether these intragenic binding sites represent active promoters. Here, we construct and assay transcriptional promoter-lacZ fusions for all 52 putative FliA promoters previously identified by ChIP-seq. These experiments, coupled with integrative analysis of published genome-scale transcriptional datasets, reveal that most intragenic FliA binding sites are active promoters that transcribe highly unstable RNAs. Additionally, we show that widespread intragenic FliA-dependent transcription is a conserved phenomenon, but that the specific promoters are not themselves conserved. We conclude that intragenic FliA-dependent promoters and the resulting RNAs are unlikely to have important regulatory functions. Nonetheless, one intragenic FliA promoter is broadly conserved, and constrains evolution of the overlapping protein-coding gene. Thus, our data indicate that intragenic regulatory elements can influence protein evolution in bacteria, and suggest that the impact of intragenic regulatory sequences on genome evolution should be considered more broadly.\n\nAUTHOR SUMMARYRecent genome-scale studies of bacterial transcription have revealed thousands of promoters inside genes. In a few cases, these promoters have been shown to transcribe functional RNAs. However, it is unclear whether most intragenic promoters have important biological function. Similarly, there are likely to be thousands of intragenic binding sites for transcription factors, but very few have been functionally characterized. Moreover, it is unclear what impact intragenic promoters and transcription factor binding sites have on evolution of the overlapping genes. In this study, we focus on FliA, a broadly conserved Sigma factor that is responsible for initiating transcription of many flagellar genes. We previously showed that FliA directs RNA polymerase to ~50 genomic sites in Escherichia coli. In our current study, we show that while most intragenic FliA promoters are actively transcribed, very few are conserved in other species. This suggests that most FliA promoters are not functional. Nonetheless, one intragenic FliA promoter is highly conserved, and we show that this promoter constrains evolution of the overlapping protein-coding gene. Given the enormous number of regulatory DNA sites within genes, we propose that the evolution of many genes is constrained by these elements.

genetics↗

bioRxiv2017

Determining the Specificity of Cascade Binding, Interference, and Priming in vivo

In CRISPR-Cas immunity systems, short CRISPR RNAs (crRNAs) are bound by CRISPR-associated (Cas) proteins, and these complexes target invading nucleic acid molecules for degradation in a process known as interference. In type I CRISPR-Cas systems, the Cas protein complex that binds DNA is known as Cascade. Association of Cascade with target DNA can also lead to acquisition of new immunity elements in a process known as primed adaptation. Here, we assess the specificity determinants for Cascade-DNA interaction, interference, and primed adaptation in vivo, for the type I-E system of Escherichia coli. Remarkably, as few as 5 bp of crRNA-DNA are sufficient for association of Cascade with a DNA target. Consequently, a single crRNA promotes Cascade association with numerous off-target sites, and the endogenous E. coli crRNAs direct Cascade binding to >100 chromosomal sites. In contrast to the low specificity of Cascade-DNA interactions, >18 bp are required for both interference and primed adaptation. Hence, Cascade binding to sub-optimal, off-target sites is inert. Our data support a model in which initial Cascade association with DNA targets requires only limited sequence complementarity at the crRNA 5{square} end, whereas recruitment and/or activation of the Cas3 nuclease, a prerequisite for interference and primed adaptation, requires extensive base-pairing.\n\nIMPORTANCEMany bacterial and archaeal species encode CRISPR-Cas immunity systems that protect against invasion by foreign DNA. In the Escherichia coli CRISPR-Cas system, a protein complex, Cascade, binds 61 nt CRISPR RNAs (crRNAs). The Cascade complex is directed to invading DNA molecules through base-pairing between the crRNA and target DNA. This leads to recruitment of the Cas3 nuclease that destroys the invading DNA molecule and promotes acquisition of new immunity elements. We make the first in vivo measurements of Cascade binding to DNA targets. Thus, we show that Cascade binding to DNA is highly promiscuous; endogenous E. coli crRNAs can direct Cascade binding to >100 chromosomal locations. By contrast, we show that target degradation and acquisition of new immunity elements requires highly specific association of Cascade with DNA, limiting CRISPR-Cas function to the appropriate targets.

microbiology↗

bioRxiv2016

Nus factors have a widespread regulatory function in bacteria

Nus factors are broadly conserved across bacterial species, and are often essential for viability. A complex of five Nus factors (NusB, NusE, NusA, NusG and SuhB) is considered to be a dedicated regulator of ribosomal RNA folding, and has been shown to prevent Rho-dependent transcription termination. We have established the first cellular function for the Nus factor complex beyond regulation of ribosomal assembly: repression of the Nus factor-encoding gene, suhB. This repression occurs by translation inhibition followed by Rho-dependent transcription termination. Thus, the Nus factor complex can prevent or promote Rho activity depending on the gene context. Extensive conservation of NusB/E binding sites upstream of nus factor genes suggests that Nus factor autoregulation occurs in many species. Putative NusB/E binding sites are also found upstream of many other genes in diverse species, and we demonstrate Nus factor regulation of one such gene in Citrobacter koseri. We conclude that Nus factors have an evolutionarily widespread regulatory function beyond ribosomal RNA, and that they are often autoregulatory.

microbiology↗