Biology subjects

Williams, M.

Publications and source records attributed to Williams, M..

At least 73 records · Page 4Linked to original sources

bioRxiv2020

Trade-Offs Between Antibacterial Resistance and Fitness Cost in the Production of Metallo-β-Lactamase by Enteric Bacteria Manifest as Sporadic Emergence of Carbapenem Resistance in a Clinical Setting.

Meropenem is a clinically important antibacterial reserved for treatment of multi-resistant infections. In meropenem-resistant bacteria of the family Enterobacteriales, NDM-1 is considerably more common than IMP-1, despite both metallo-{beta}-lactamases (MBLs) hydrolysing meropenem with almost identical kinetics. We show that blaNDM-1 consistently confers meropenem resistance in wild-type Enterobacteriales, but blaIMP-1 does not. The reason is higher blaNDM-1 expression because of its stronger promoter. However, the cost of meropenem resistance is reduced fitness of blaNDM-1 positive Enterobacteriales because of amino acid starvation. In parallel, from a clinical case, we identified multiple Enterobacter spp. isolates carrying a plasmid-encoded blaNDM-1 having a modified promoter region. This modification lowered MBL production to a level associated with zero fitness cost but, consequently, the isolates were not meropenem resistant. However, we identified a Klebsiella pneumoniae isolate from this same clinical case carrying the same blaNDM-1 plasmid. This isolate was meropenem resistant despite low-level NDM-1 production because of a ramR mutation, reducing envelope permeability. Overall, therefore, we show how the resistance/fitness trade-off for MBL carriage can be resolved. The result is sporadic emergence of meropenem resistance in a clinical setting.

microbiology↗

bioRxiv2020

dN/dS dynamics quantify tumour immunogenicity and predict response to immunotherapy

Immunoediting is a major force during cancer evolution that selects for clones with low immunogenicity (adaptation), or clones with mechanisms of immune evasion (escape). However, quantifying immunogenicity in the cancer genome and how the tumour-immune coevolutionary dynamics impact patient outcomes remain unexplored. Here we show that the ratio of nonsynonymous to synonymous mutations (dN/dS) in the immunopeptidome quantifies tumor immunogenicity and differentiates between adaptation and escape. We analysed 8,543 primary tumors from TCGA and validated immune dN/dS as a measure of selection associated with immune infiltration in immune-adapted tumours. In a cohort of 308 metastatic patients that received immunotherapy, pre-treatment lesions in non-responders showed increased immune selection (dN/dS<1), whereas responders did not and instead harboured a higher proportion of genetic escape mechanisms. Ultimately, these findings highlight the potential of evolutionary genomic measures to predict clinical response to immunotherapy.

genomics↗

bioRxiv2020

Long-read genome sequencing for the diagnosis of neurodevelopmental disorders

PurposeExome and genome sequencing have proven to be effective tools for the diagnosis of neurodevelopmental disorders (NDDs), but large fractions of NDDs cannot be attributed to currently detectable genetic variation. This is likely, at least in part, a result of the fact that many genetic variants are difficult or impossible to detect through typical short-read sequencing approaches. MethodsHere, we describe a genomic analysis using Pacific Biosciences circular consensus sequencing (CCS) reads, which are both long (>10 kb) and accurate (>99% bp accuracy). We used CCS on six proband-parent trios with NDDs that were unexplained despite extensive testing, including genome sequencing with short reads. ResultsWe identified variants and created de novo assemblies in each trio, with global metrics indicating these data sets are more accurate and comprehensive than those provided by short-read data. In one proband, we identified a likely pathogenic (LP), de novo L1-mediated insertion in CDKL5 that results in duplication of exon 3, leading to a frameshift. In a second proband, we identified multiple large de novo structural variants, including insertion-translocations affecting DGKB and MLLT3, which we show disrupt MLLT3 transcript levels. We consider this extensive structural variation likely pathogenic. ConclusionThe breadth and quality of variant detection, coupled to finding variants of clinical and research interest in two of six probands with unexplained NDDs strongly support the value of long-read genome sequencing for understanding rare disease.

genomics↗

bioRxiv2020

Factors Influencing Precision Medicine Knowledge and Attitudes

Precision medicine holds great promise for improving health and reducing health disparities that can be most fully realized by advancing diversity and inclusion in research participants. Without engaging underrepresented groups, precision medicine could not only fail to achieve its promise but also further exacerbate the health disparities already burdening the most vulnerable. Yet underrepresentation by people of non-European ancestry continues in precision medicine research and there are disparities across racial groups in the uptake of precision medicine applications and services. Studies have explored possible explanations for population differences in precision medicine participation, but full appreciation of the factors involved is still developing. To better inform the potential for addressing health disparities through PM, we assessed the relationship of precision medicine knowledge and trust in biomedical research with sociodemographic variables. Using a series of linear regression models applied to survey data collected in a diverse sample, we analyzed variation in both precision medicine knowledge and trust in biomedical research with socioeconomic factors as a way to understand the range of precision medicine knowledge (PMK) in a broadly representative group and its relationship to trust in research and demographic characteristics. Our results demonstrate that identifying as Black, while significantly PMK, explains only 1.5% of the PMK variance in unadjusted models and 7% of overall variance in models adjusted for meaningful covariates such as age, marital status, employment, and education. We also found a positive association between PMK and trust in biomedical research. These results indicate that race is a factor affecting PMK, even after accounting for differences in sociodemographic variables. Additional work is needed, however, to identify other factors contributing to variation in PMK as we work to increase diversity and inclusion in precision medicine applications.

genetics↗

bioRxiv2020

Single cell fitness landscapes induced by genetic and pharmacologic perturbations in cancer

Tumour fitness landscapes underpin selection in cancer, impacting etiology, evolution and response to treatment. Progress in defining fitness landscapes has been impeded by a lack of timeseries perturbation experiments over realistic intervals at single cell resolution. We studied the nature of clonal dynamics induced by genetic and pharmacologic perturbation with a quantitative fitness model developed to ascribe quantitative selective coefficients to individual cancer clones, enable prediction of clone-specific growth potential, and forecast competitive clonal dynamics over time. We applied the model to serial single cell genome (>60,000 cells) and transcriptome (>58,000 cells) experiments ranging from 10 months to 2.5 years in duration. We found that genetic perturbation of TP53 in epithelial cell lines induces multiple forms of copy number alteration that confer increased fitness to clonal populations with measurable consequences on gene expression. In patient derived xenografts, predicted selective coefficients accurately forecasted clonal competition dynamics, that were validated with timeseries sampling of experimentally engineered mixtures of low and high fitness clones. In cisplatin-treated patient derived xenografts, the fitness landscape was inverted in a time-dependent manner, whereby a drug resistant clone emerged from a phylogenetic lineage of low fitness clones, and high fitness clones were eradicated. Moreover, clonal selection mediated reversible drug response early in the selection process, whereas late dynamics in genomically fixed clones were associated with transcriptional plasticity on a fixed clonal genotype. Together, our findings outline causal mechanisms with implication for interpreting how mutations and multi-faceted drug resistance mechanisms shape the etiology and cellular fitness of human cancers.

cancer biology↗

bioRxiv2020

Efficient Bayesian inference of phylogenetic trees from large scale, low-depth genome-wide single-cell data

A new generation of scalable single cell whole genome sequencing (scWGS) methods allows unprecedented high resolution measurement of the evolutionary dynamics of cancer cell populations. Phylogenetic reconstruction is central to identifying sub-populations and distinguishing the mutational processes that gave rise to them. Existing phylogenetic tree building models do not scale to the tens of thousands of high resolution genomes achievable with current scWGS methods. We constructed a phylogenetic model and associated Bayesian inference procedure, sitka, specifically for scWGS data. The method is based on a novel phylogenetic encoding of copy number (CN) data, the sitka transformation, that simplifies the site dependencies induced by rearrangements while still forming a sound foundation to phylogenetic inference. The sitka transformation allows us to design novel scalable Markov chain Monte Carlo (MCMC) algorithms. Moreover, we introduce a novel point mutation calling method that incorporates the CN data and the underlying phylogenetic tree to overcome the low per-cell coverage of scWGS. We demonstrate our method on three single cell datasets, including a novel PDX series, and analyse the topological properties of the inferred trees. Sitka is freely available at https://github.com/UBC-Stat-ML/sitkatree.git.

bioinformatics↗

bioRxiv2020

Using seedling phenotypic traits to select local seed sources for large-scale restoration: methods and outcomes in a Great Basin case study

Establishing plants from seed is often a limitation to restoration success in semi-arid systems. For restoration purposes, managers can either use widely-available commercial seeds, which are often sourced from far outside the seeding area, or take extra steps to use locally collected seeds. If local seeds have traits more conducive to seedling establishment in degraded sites, they could increase restoration success. Here, we asked whether wild-collected seeds of two native perennial grasses, Elymus elymoides and Poa secunda, had more favorable characteristics than commercial sources. Seeds were collected from four populations within the Winnemucca District of the Nevada Bureau of Land Management, which manages lands within the Great Basin, US. Collections were screened for seed and seedling characteristics associated with increased plant performance in invaded Great Basin systems, and we provide a detailed methodology for these measurements. Relative to commercial seeds, wild-collected seeds had more characteristics identified as beneficial for seedling establishment including earlier emergence, higher specific root length, more root tips, and smaller overall size (E. elymoides), and earlier emergence, longer roots, higher root mass ratio, and more root tips (P. secunda). Commercial sources had significantly larger seeds than wild populations, a trait that had mixed effects on performance in previous research, and one that may change as wild collections are increased in agronomic conditions. These results suggest that locally-sourced populations are more likely to perform well in invaded areas, providing support for efforts to collect, screen, and increase local sources of seeds to improve restoration success. Implications for PracticeO_LICollecting and increasing local seeds requires more time and effort than purchasing commercially-available seeds, but if these sources have a greater chance at surviving in restoration sites, this effort is warranted C_LIO_LIIn our study, remnant local populations possessed more potentially adaptive traits than commercially-available alternatives, indicating they may be superior sources for the restoration of disturbed sites in their local regions C_LIO_LIScreening multiple seed sources for potentially adaptive seed and seedling traits can be a relatively quick and effective way to select the most promising seeds for increase C_LI

ecology↗

bioRxiv2020

Ancient human genomes reveal a hidden history of strong selection in Eurasia

The role of natural selection in shaping biological diversity is an area of intense interest in modern biology. To date, studies of positive selection have primarily relied upon genomic datasets from contemporary populations, which are susceptible to confounding factors associated with complex and often unknown aspects of population history. In particular, admixture between diverged populations can distort or hide prior selection events in modern genomes, though this process is not explicitly accounted for in most selection studies despite its apparent ubiquity in humans and other species. Through analyses of ancient and modern human genomes, we show that previously reported Holocene-era admixture has masked more than 50 historic hard sweeps in modern European genomes. Our results imply that this canonical mode of selection has likely been underappreciated in the evolutionary history of humans and suggests that our current understanding of the tempo and mode of selection in natural populations may be quite inaccurate.

genomics↗

bioRxiv2020

Stabilising selection causes grossly altered but stable karyotypes in metastatic colorectal cancer

Aneuploidy, the loss and gain of whole and part chromosomes, is near-ubiquitous in cancer genomes and likely defines cancer cell biology. However, the temporal evolutionary dynamics that select for aneuploidy remain uncharacterised. Here we perform longitudinal genomic analysis of 755 samples from a total of 167 patients with colorectal-derived neoplastic lesions that represent distinct stages of tumour evolution through metastasis and treatment. Adenomas typically had few copy number alterations (CNAs) and most were subclonal, whereas cancers had many clonal CNAs, suggesting that progression goes through a CNA bottleneck. Individual CRC glands from the same tumour typically had very similar karyotypes, despite evidence of ongoing instability at the cell level in patient tumours, cell lines and organoids. CNAs in metastatic lesions sampled from liver and other organs, after chemotherapy or targeted therapies, and in late recurrences were typically similar to the primary tumour. Mathematical modelling and statistical inference indicated that these data are consistent with the action of negative selection on CNAs that traps cancer cell genomes on a fitness peak defined by the specific pattern of chromosomal aberrations. These data suggest that the initial progression of colorectal cancer requires the traversal of a rugged fitness landscape and subsequent CNA evolution, including metastatic dissemination and therapeutic resistance, is constrained by negative selection.

cancer biology↗

bioRxiv2019

Self-regulation of single-stranded DNA wrapping dynamics by E. coli SSB promotes both stable binding and rapid dissociation

E. coli SSB (EcSSB) is a model protein for studying functions of single-stranded DNA (ssDNA) binding proteins (SSBs), which are critical in genome maintenance. EcSSB forms homotetramers that wrap ssDNA in multiple conformations in order to protect these transiently formed regions during processes such as replication and repair. Using optical tweezers, we measure the binding and wrapping of a single long ssDNA substrate under various conditions and free protein concentrations. We show that EcSSB binds in a biphasic manner, where initial wrapping events are followed by unwrapping events as protein density on the substrate passes a critical saturation. Increasing free EcSSB concentrations increase the fraction of EcSSBs in less-wrapped conformations, including a previously uncharacterized EcSSB8 bound state in which [~]8 nucleotides of ssDNA are bound by a single domain of the tetramer with minimal substrate deformation. When the ssDNA is over-saturated with EcSSB, stimulated dissociation rapidly removes excess EcSSB, leaving an array of stably-wrapped EcSSB-ssDNA complexes. We develop a multi-step kinetic model in which EcSSB tetramers transition through multiple wrapped conformations which are regulated through nearest neighbor interactions and ssDNA occupancy. These results provide a mechanism through which otherwise stably bound and wrapped EcSSB tetramers can be rapidly removed from an ssDNA substrate to allow for DNA maintenance and replication functions while still fully protecting ssDNA over a wide range of protein concentrations.

biophysics↗

bioRxiv2019

The Habenular Receptor GPR151 Regulates Addiction Vulnerability Across Drug Classes

The habenula controls the addictive properties of nicotine but also densely expresses opioid and cannabinoid receptors. As such, identification of strategies to manipulate habenular activity may yield new approaches to treat substance use disorders. Here we show that GPR151, an orphan G protein-coupled receptor (GPCR) highly enriched in the habenula of humans and rodents plays a critical role in regulating habenular function and behavioral responses to addictive drugs. We show that GPR151 is expressed on axonal and presynaptic membranes and synaptic vesicles, and regulates synaptic fidelity and plasticity. We find that GPR151 associates with synaptic components controlling vesicle release and ion transport and couples to the G-alpha inhibitory protein Go1 to reduce cAMP levels. Stable cell lines expressing GPR151 confirm that it signals via Gi/o and are amenable to ligand screens. Gpr151 null mice show diminished behavioral responses to nicotine, and self-administer greater quantities of the drug, phenotypes rescued by viral re-expression of Gpr151 in the habenula. Gpr151 null mice are also insensitive to the behavioral actions of morphine and cannabinoids. These data identify GPR151 as a critical modulator of habenular function that controls addiction vulnerability across different drug classes.\n\nHighlightsO_LIHabenula neurons are enriched in nicotinic, opioid, cannabinoid and GPR151 receptors\nC_LIO_LIGPR151 modulates synaptic fidelity and release probability at habenular terminals.\nC_LIO_LIHabenular GPR151 plays a role in drug abuse and food intake/weight control\nC_LIO_LIGPR151 couples to the G-alpha inhibitory protein Go1 to reduce cAMP levels.\nC_LI\n\neTOC BlurbAntolin-Fontes at al. identify a G protein-coupled receptor, GPR151, which is highly enriched in human habenular neurons. These neurons are primarily enriched with nicotinic, opioid and cannabinoid receptors. We find that GPR151 modulates habenular synaptic vesicle release probability and behavioral responses to these drugs of abuse.

neuroscience↗

bioRxiv2019

Characterisation of cefotaxime-resistant urinary Escherichia coli from primary care in South-West England 2017-2018.

ObjectivesThird-generation cephalosporin-resistant Escherichia coli from community-acquired urinary tract infections (UTI) have been increasingly reported worldwide. In this study we sought to determine and characterise the mechanisms of cefotaxime-resistance (CTX-R) employed by urinary E. coli obtained from primary care over a 12-month period, in Bristol and surrounding counties in the South West of England.\n\nMethodsCephalexin resistant (Ceph-R) E. coli isolates were identified directly from general practice (GP) referred urine samples using disc susceptibility testing as per standard diagnostic procedures. CTX-R was determined by subsequent plating onto MIC breakpoint plates. {beta}-Lactamase genes were detected by PCR. Whole Genome Sequencing (WGS) was performed on 225 urinary isolates and analyses were performed using the Centre for Genomic Epidemiology platform. Patient information provided by the referring GPs was reviewed.\n\nResultsDuring the study period, Ceph-R E. coli (n=900) were obtained directly from urines from 146 GPs. Seventy-percent (626/900) of isolates were CTX-R. WGS of 225 non-duplicate isolates identified that the most common mechanism of CTX-R was blaCTX-M carriage (185/225; 82.2%), predominantly blaCTX-M-15 (114/185; 61.6%), followed by carriage of plasmid mediated AmpCs (pAmpCs) (17/225; 7.6%), ESBL blaSHV variants (6/225; 2.7%), AmpC hyperproduction (13/225; 5.8%), or a combination of both blaCTX-M and pAmpC carriage (4/225; 1.8%). Forty-four sequence types (STs) were identified with ST131 representing 101/225 (45.0%) of sequenced isolates, within which the blaCTX-M-15-positive clade C2 was dominant (54/101; 53.5%). Ciprofloxacin-resistance (CIP-R) was observed in 128/225 (56.9%) of sequenced CTX-R isolates - predominantly associated with fluoroquinolone-resistant clones ST131 and ST1193.\n\nConclusionsMost Ceph-R urinary E. colis were CTX-R, predominantly caused by blaCTX-M carriage. There was a clear correlation between CTX-R and CIP-R, largely attributable to the dominance of the high-risk pandemic clones, ST131 and ST1193 in this study. This localised epidemiological data provides greater resolution than regional data and can be valuable for informing treatment choices in the primary care setting.

microbiology↗

bioRxiv2019

A workflow for visualizing human cancer biopsies using large-format electron microscopy

Recent developments in large format electron microscopy have enabled generation of images that provide detailed ultrastructural information on normal and diseased cells and tissues. Analyses of these images increase our understanding of cellular organization and interactions and disease-related changes therein. In this manuscript, we describe a workflow for two-dimensional (2D) and three-dimensional (3D) imaging, including both optical and scanning electron microscopy (SEM) methods, that allow pathologists and cancer biology researchers to identify areas of interest from human cancer biopsies. The protocols and mounting strategies described in this workflow are compatible with 2D large format EM mapping, 3D focused ion beam-SEM and serial block face-SEM. The flexibility to use diverse imaging technologies available at most academic institutions makes this workflow useful and applicable for most life science samples. Volumetric analysis of the biopsies studied here revealed morphological, organizational and ultrastructural aspects of the tumor cells and surrounding environment that cannot be revealed by conventional 2D EM imaging. Our results indicate that although 2D EM is still an important tool in many areas of diagnostic pathology, 3D images of ultrastructural relationships between both normal and cancerous cells, in combination with their extracellular matrix, enables cancer researchers and pathologists to better understand the progression of the disease and identify potential therapeutic targets.

cancer biology↗

bioRxiv2019

Measuring the distribution of fitness effects in somatic evolution by combining clonal dynamics with dN/dS ratios

The distribution of fitness effects (DFE) defines how new mutations spread through an evolving population. The ratio of non-synonymous to synonymous mutations (dN/dS) has become a popular method to detect selection in somatic cells, however the link, in somatic evolution, between dN/dS values and fitness coefficients is missing. Here we present a quantitative model of somatic evolutionary dynamics that yields the selective coefficients from individual driver mutations from dN/dS estimates, and then measure the DFE for somatic mutant clones in ostensibly normal oesophagus and skin. We reveal a broad distribution of fitness effects, with the largest fitness increases found for TP53 and NOTCH1 mutants (proliferative bias 1-5%). Accurate measurement of the per-gene DFE in cancer evolution is precluded by the quality of currently available sequencing data. This study provides the theoretical link between dN/dS values and selective coefficients in somatic evolution, and reveals the DFE for mutations in human tissues.

bioinformatics↗

bioRxiv2019

A humanness dimension to visual object coding in the brain

Neuroimaging studies investigating human object recognition have largely focused on a relatively small number of object categories, in particular, faces, bodies, scenes, and vehicles. More recent studies have taken a broader focus, investigating hypothesised dichotomies, for example animate versus inanimate, and continuous feature dimensions, such as biologically similarity. These studies typically have used stimuli that are clearly identified as animate or inanimate, neglecting objects that may not fit into this dichotomy. We generated a novel stimulus set including standard objects and objects that blur the animate-inanimate dichotomy, for example robots and toy animals. We used MEG time-series decoding to study the brains emerging representation of these objects. Our analysis examined contemporary models of object coding such as dichotomous animacy, as well as several new higher order models that take into account an objects capacity for agency (i.e. its ability to move voluntarily) and capacity to experience the world. We show that early brain responses are best accounted for by low-level visual similarity of the objects; and shortly thereafter, higher order models of agency/experience best explained the brains representation of the stimuli. Strikingly, a model of human-similarity provided the best account for the brains representation after an initial perceptual processing phase. Our findings provide evidence for a new dimension of object coding in the human brain - one that has a \"human-centric\" focus.

neuroscience↗

bioRxiv2019

Discovery, Expression, Cellular Localization, and Molecular Properties of a Novel, Alternative Spliced HP1g Isoform, Lacking the Chromoshadow Domain

By reading the H3K9Me3 mark through their N-terminal chromodomain (CD), HP1 proteins play a significant role in cancer-associated processes, including cell proliferation, differentiation, chromosomal stability, and DNA repair. Here, we used a combination of bioinformatics-based methodologies, as well as experimentally-derived datasets, that reveal the existence of a novel short HP1{gamma} (CBX3) isoform, named here sHP1{gamma}, generated by alternative splicing of the CBX3 locus. The sHP1{gamma} mRNA encodes a protein composed of 101 residues and lacks the C-terminal chromoshadow domain (CSD) that is required for dimerization and heterodimerization in the previously described 183 a. a HP1{gamma} protein. Fold recognition, order-to-disorder calculations, threading, homology-based molecular modeling, docking, and molecular dynamic simulations show that the sHP1{gamma} is comprised of a CD flanked by intrinsically disordered regions (IDRs) with an IDR-CD-IDR domain organization and likely retains the ability to bind to the H3K9Me3. Both qPCR analyses and mRNA-seq data derived from large-scale studies confirmed that sHP1{gamma} mRNA is expressed in the majority of human tissues at approximately constant ratios with the chromoshadow domain containing isoform. However, sHP1{gamma} mRNA levels appear to be dysregulated in different cancer types. Thus, our data supports the notion that, due to the existence of functionally different isoforms, the regulation of HP1{gamma}-mediated functions is more complex than previously anticipated.

molecular biology↗

bioRxiv2019

Model-based tumor subclonal reconstruction

The vast majority of cancer next-generation sequencing data consist of bulk samples composed of mixtures of cancer and normal cells. To study tumor evolution, subclonal reconstruction approaches based on machine learning are used to separate subpopulation of cancer cells and reconstruct their ancestral relationships. However, current approaches are entirely data-driven and agnostic to evolutionary theory. We demonstrate that systematic errors occur in subclonal reconstruction if tumor evolution is not accounted for, and that those errors increase when multiple samples are taken from the same tumor. To address this issue, we present a novel approach for model-based subclonal reconstruction that combines data-driven machine learning with evolutionary theory. Using public, synthetic and newly generated data, we show the method is more robust and accurate than current techniques in both single-sample and multi-region sequencing data. With careful data curation and interpretation, we show how the method allows minimizing the confounding factors that affect non-evolutionary methods, leading to a more accurate recovery of the evolutionary history of human tumors.

bioinformatics↗

bioRxiv2019

Anopheles gambiae TEP1 forms a complex with the coiled-coil domain of LRIM1/APL1C following a conformational change in the thioester domain

The complement-like protein thioester-containing protein 1 (TEP1) is a key factor in the immune response of the malaria vector Anopheles gambiae to pathogens. Multiple allelic variants of TEP1 have been identified in laboratory strains and in the field, and are correlated with distinct immunophenotypes. TEP1 is tightly regulated by conformational changes induced by cleavage in a protease-sensitive region. Cleaved TEP1 forms a soluble complex with a heterodimer of two leucine-rich repeat proteins, LRIM1 and APL1C, and precipitates in the absence of this complex. The molecular structure and oligomeric state of the TEP1/LRIM1/APL1C complex is unclear. We have analyzed the stability of the cleaved form of four TEP1 alleles. Soluble TEP1 forms exhibit significant variation in stability from hours to days at room temperature. Stability is correlated with allelic variation within two specific loops in direct proximity to the thioester bond. The variable loops are part of an interface between the TED and MG8 domains TEP1 that protect the thioester from hydrolysis. Engineering specific disulfide bonds to prevent separation of the TED-MG8 interface stabilizes the cleaved form of TEP1 for months at room temperature. The C-terminal coiled-coil domain of the LRIM1/APL1C complex is sufficient to stabilize the cleaved form of TEP1 in solution but cleaved forms of disulfide-stabilized TEP1 do not interact with LRIM1/APL1C. This implies that formation of the TEP1cut/LRIM1/APL1C complex is dependent on the same conformational change that induces the precipitation of cleaved TEP1. Author SummaryThe mosquito Anopheles gambiae is the principal vector for malaria in Sub-Saharan Africa. A mosquitos own immune system affects how readily it transmits disease. A protein in A. gambiae called TEP1 is responsible for targeting malaria parasites that traverse the mosquitos midgut. TEP1 has multiple alleles and some are associated with a stronger immune response to malaria than others. How genetic variability in TEP1 is linked to phenotypic diversity is not understood. We show that the variation between TEP1 alleles affects the stability of the protein in solution. We also show that the different TEP1 alleles have a wide range in stability of the protein, from hours to days. Engineering disulfide bonds into TEP1 can increase this stability to months. TEP1 activity in vivo is maintained by a complex of two leucine-rich proteins called LRIM1 and APL1C, which binds TEP1 through its C-terminal coiled-coil domain. We found that LRIM1/APL1C does not bind disulfide-stabilized TEP1, suggesting that LRIM1/APL1C binds to activated TEP1. This research advances our molecular understanding of a key immune response that affects the capacity of A. gambiae mosquitoes to transmit malaria.

immunology↗