Biology subjects

Camacho, D. M.

Publications and source records attributed to Camacho, D. M..

6 recordsLinked to original sources

bioRxiv2021

Enhancers of host immune tolerance to bacterial infection discovered using linked computational and experimental approaches

Current therapeutic strategies against bacterial infections focus on reduction of pathogen load through antibiotics; however, stimulation of host tolerance to infection might offer an alternative approach. Here we used computational transcriptomics and a Xenopus embryo infection model to rapidly discover infection response pathways, identify potential tolerance inducer drugs, and validate their ability to induce broad tolerance. Xenopus embryos exhibit natural tolerance to A. baumanii, K. pneumoniae, S. aureus, and S. pneumoniae bacteria, whereas A. hydrophila and P. aeruginosa produce infection that leads to death. Transcriptional profiling led to definition of a 20-gene signature that allows for discrimination between tolerant and susceptible states, as well as identification of active and passive tolerance responses based on the degree of engagement of gene transcription modulation. Upregulation of metal ion transport and hypoxia pathways reminiscent of responses observed in primate and mouse infection models were identified as tolerance mediators, and drug screening in the susceptible A. hydrophila infection model confirmed that a metal chelator (deferoxamine) and HIF-1 agonist (1,4-DPCA) increase embryo survival despite high pathogen load. These data demonstrate the value of combining the Xenopus embryo infection model with multi-omics analyses for mechanistic discovery and drug repurposing to induce host tolerance to bacterial infection.

immunology↗

bioRxiv2020

SweetOrigins: Extracting Evolutionary Information from Glycans

Glycans, the most diverse biopolymer and crucial for many biological processes, are shaped by evolutionary pressures stemming in particular from host-pathogen interactions. While this positions glycans as being essential for understanding and targeting host-pathogen interactions, their considerable diversity and a lack of methods has hitherto stymied progress in leveraging their predictive potential. Here, we utilize a curated dataset of 12,674 glycans from 1,726 species to develop and apply machine learning methods to extract evolutionary information from glycans. Our deep learning-based language model SweetOrigins provides evolution-informed glycan representations that we utilize to discover and investigate motifs used for molecular mimicry-mediated immune evasion by commensals and pathogens. Novel glycan alignment methods enable us to identify and contextualize virulence-determining motifs in the capsular polysaccharide of Staphylococcus aureus and Acinetobacter baumannii. Further, we show that glycan-based phylogenetic trees contain most of the information present in traditional 16S rRNA-based phylogenies and improve on the differentiation of genetically closely related but phenotypically divergent species, such as Bacillus cereus and Bacillus anthracis. Leveraging the evolutionary information inherent in glycans with machine learning methodology is poised to provide further - critically needed - insights into host-pathogen interactions, sequence-to-function relationships, and the major influence of glycans on phenotypic plasticity.

bioinformatics↗

bioRxiv2020

Using Natural Language Processing to Learn the Grammar of Glycans

While nucleic acids and proteins receive ample attention, progress on understanding the structural and functional roles of carbohydrates has lagged behind. Here, we develop a language model for glycans, SweetTalk, taking into account glycan connectivity and composition. We use this model to investigate motifs in glycan substructures, classify them according to their O-/N-linkage, and predict their immunogenicity with an accuracy of [~]92%, opening up the potential for rational glycoengineering.

bioinformatics↗

bioRxiv2019

Sequence-to-function deep learning frameworks for synthetic biology

While synthetic biology has revolutionized our approaches to medicine, agriculture, and energy, the design of novel circuit components beyond nature-inspired templates can prove itself challenging without well-established design rules. Toehold switches -- programmable nucleic acid sensors -- face an analogous prediction and design bottleneck: our limited understanding of how sequence impacts functionality can require expensive, time-consuming screens for effective switches. Here, we introduce the Sequence-based Toehold Optimization and Redesign Model (STORM), a deep learning architecture that applies gradient ascent to re-engineer poorly-performing toeholds. Based on a dataset of 91,534 toehold switches, we examined convolutional filters and saliency maps of sequences to interpret our sequence-to-function model, identifying hot spots where mutations change toehold effectiveness and features unique to high-performing switches. Our modeling platform provides frameworks for future toehold selection, augmenting our ability to construct potent synthetic circuit components and precision diagnostics, and enabling straightforward translation of this in silico workflow to other circuitries.

synthetic biology↗

bioRxiv2019

Species-specific enhancement of enterohemorrhagic E. Coli pathogenesis mediated by microbiome metabolites

BackgroundSpecies-specific differences in tolerance to infection are exemplified by the high susceptibility of humans to enterohemorrhagic E. coli (EHEC) infection whereas mice are relatively resistant to this pathogen. This intrinsic species-specific difference in EHEC infection limits the translation of murine research to human. Furthermore, studying the mechanisms underlying this differential susceptibility is a difficult problem due to complex in vivo interactions between the host, pathogen, and disparate commensal microbial communities.\n\nResultsWe utilize organ-on-a-chip (Organ Chip) microfluidic culture technology to model damage of the human colonic epithelium induced by EHEC infection, and show that epithelial injury is greater when exposed to metabolites derived from the human gut microbiome compared to mouse. Using a multi-omics approach, we discovered four human microbiome metabolites -- 4-methyl benzoic acid, 3,4-dimethylbenzoic acid, hexanoic acid, and heptanoic acid -- that are sufficient to mediate this effect. The active human microbiome metabolites preferentially induce expression of flagellin, a bacterial protein associated with motility of EHEC and increased epithelial injury. Thus, the decreased tolerance to infection observed in humans versus other species may be due in part to the presence of compounds produced by the human intestinal microbiome that actively promote bacterial pathogenicity.\n\nConclusionOrgan on chip technology allowed the identification of specific human microbiome metabolites modulating EHEC pathogenesis. These identified metabolites are sufficient to increase susceptibility to EHEC in our human Colon Chip model and they contribute to species-specific tolerance. This work suggests that higher concentrations of these metabolites could be the reason for higher susceptibility to EHEC infection in certain human populations, such as children. Furthermore, this research lays the foundation for therapeutic-modulation of microbe products in order to prevent and treat human bacterial infection.

bioengineering↗

bioRxiv2018

Complex human gut microbiome cultured in anaerobic human intestine chips

The diverse bacterial populations that comprise the commensal microbiota of the human intestine play a central role in health and disease, yet no method is available to sustain these complex microbial communities in direct contact with living human intestinal cells and their overlying mucus layer in vitro. Here we describe a human Organ-on-a-Chip (Organ Chip) microfluidic platform that permits control and real-time assessment of physiologically-relevant oxygen gradients, and which enables co-culture of living human intestinal epithelium with stable communities of aerobic and anaerobic human gut microbiota. When compared to aerobic co-culture conditions, establishment of a transluminal hypoxia gradient sustained higher microbial diversity with over 200 unique operational taxonomic units (OTUs) from 11 different genera, and an abundance of obligate anaerobic bacteria with ratios of Firmicutes and Bacteroidetes similar to those observed in human feces, in addition to increasing intestinal barrier function. The ability to culture human intestinal epithelium overlaid by complex human gut microbial communities within microfluidic Intestine Chips may enable investigations of host-microbiome interactions that were not possible previously, and serve as a discovery tool for development of new microbiome-related therapeutics, probiotics, and nutraceuticals.

bioengineering↗