Biology subjects

Oliver, A.

Publications and source records attributed to Oliver, A..

At least 37 records · Page 2Linked to original sources

bioRxiv2023

Quantitative Assessment of Morphological Changes in Lipid Droplets and Lipid-Mito Interactions with Aging in Brown Adipose

The physical characteristics of brown adipose tissue (BAT) are defined by the presence of multilocular lipid droplets (LD) within the brown adipocytes and a high abundance of iron-containing mitochondria, which give it its characteristic color. Normal mitochondrial function is, in part, regulated by organelle-to-organelle contacts. Particularly, the contact sites that mediate mitochondria-LD interactions are thought to have various physiological roles, such as the synthesis and metabolism of lipids. Aging is associated with mitochondrial dysfunction, and previous studies show that there are changes in mitochondrial structure and proteins that modulate organelle contact sites. However, how mitochondria-LD interactions change with aging has yet to be fully clarified. Therefore, we sought to define age-related changes in LD morphology and mitochondria-lipid interactions in BAT. We examined the three-dimensional morphology of mitochondria and LDs in young (3-month) and aged (2-year) murine BAT using serial block face-scanning electron microscopy and the Amira program for segmentation, analysis, and quantification. Analysis showed reductions in LD volume, area, and perimeter in aged samples compared to young samples. Additionally, we observed changes in LD appearance and type in aged samples compared to young samples. Notably, we found differences in mitochondrial interactions with LDs, which could implicate that these contacts may be important for energetics in aging. Upon further investigation, we also found changes in mitochondrial and cristae structure for mitochondria interacting with LD lipids. Overall, these data define the nature of LD morphology and organelle-organelle contacts during aging and provide insight into LD contact site changes that interconnect biogerontology and mitochondrial functionality, metabolism, and bioactivity in aged BAT. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=141 SRC="FIGDIR/small/559135v2_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@e5b7org.highwire.dtl.DTLVardef@e965e5org.highwire.dtl.DTLVardef@120c7e9org.highwire.dtl.DTLVardef@124bfb5_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract Workflow highlighting the process of murine interscapular BAT extraction, processing and imaging serial block facing-scanning electron microscopy and using Amira software for 3D reconstruction of LDs and mitochondrial lipid contact sites to elucidate their structure across aging. C_FIG

biophysics↗

bioRxiv2023

TaxaHFE: A machine learning approach to collapse microbiome datasets using taxonomic structure

MotivationBiologists increasingly turn to machine learning models not just to predict, but to explain. Feature reduction is a common approach to improve both performance and interpretability of models. However, some biological data sets, such as microbiome data, are inherently organized in a taxonomy, but these hierarchical relationships are not leveraged during feature reduction. We sought to design a feature engineering algorithm to exploit relationships in hierarchically organized biological data. ResultsWe designed an algorithm, called TaxaHFE, to collapse information-poor features into their higher taxonomic levels. We applied TaxaHFE to six previously published datasets and found, on average, a 90% reduction in the number of features (s.d = 5.1%) compared to using the most complete taxonomy. Using machine learning to compare the most resolved taxonomic level (i.e., species) against TaxaHFE-preprocessed features, models based on TaxaHFE features achieved an average increase of 3.47% in receiver operator curve area under the curve (ROC-AUC). Compared to other hierarchical feature engineering implementations, TaxaHFE introduces the novel ability to consider both categorical and continuous response variables to inform the feature set collapse. Importantly, we find TaxaHFEs ability to reduce hierarchically organized features to a more information-rich subset increases the interpretability of models. Availability and ImplementationTaxaHFE is available as a Docker image and as R code at https://github.com/aoliver44/taxaHFE.

bioinformatics↗

bioRxiv2023

TopBP1 utilises a bipartite GINS binding mode to activate the replicative helicase

Activation of the replicative Mcm2-7 helicase by loading GINS and Cdc45 is crucial for replication origin firing, and as such for faithful genetic inheritance. Our biochemical and structural studies demonstrate that the helicase activator GINS interacts with TopBP1 through two separate binding surfaces, the first involving a stretch of highly conserved amino acids in the TopBP1-GINI region, the second a surface on TopBP1-BRCT4. The two surfaces bind to opposite ends of the A domain of the GINS subunit Psf1. Mutation analysis reveals that either surface is individually able to support TopBP1-GINS interaction, albeit with reduced affinity. Consistently, either surface is sufficient for replication origin firing in Xenopus egg extracts and becomes essential in the absence of the other. The TopBP1-GINS interaction appears sterically incompatible with simultaneous binding of DNA polymerase epsilon (Pol{varepsilon}) to GINS when bound to Mcm2-7-Cdc45, although TopBP1-BRCT4 and the Pol{varepsilon} subunit PolE2 show only partial competitivity in binding to Psf1. Our TopBP1-GINS model improves the understanding of the recently characterised metazoan pre-loading complex. It further predicts the coordination of three molecular origin firing processes, DNA polymerase epsilon arrival, TopBP1 ejection and GINS integration into Mcm2-7-Cdc45.

molecular biology↗

bioRxiv2022

Structure of the human RAD17-RFC clamp loader and 9-1-1 checkpoint clamp bound to a dsDNA-ssDNA junction

The RAD9-RAD1-HUS1 (9-1-1) clamp forms one half of the DNA damage checkpoint system that signals the presence of substantial regions of single-stranded DNA arising from replication fork collapse or resection of DNA double strand breaks. Loaded at the 5-recessed end of a dsDNA-ssDNA junction by the RAD17-RFC clamp loader complex, the phosphorylated C-terminal tail of the RAD9 subunit of 9-1-1 engages with the mediator scaffold TOPBP1 which in turn activates the ATR kinase, localised through the interaction of its constitutive partner ATRIP with RPA-coated ssDNA. Using cryogenic electron microscopy (cryoEM) we have determined the structure of a complex of the human RAD17-RFC clamp loader bound to human 9-1-1, engaged with a dsDNA-ssDNA junction. The structure answers the key questions of how RAD17 confers specificity for 9-1-1 over PCNA, and how the clamp loader specifically recognises the recessed 5 DNA end and fixes the orientation of 9-1-1 on the ssDNA.

biochemistry↗

bioRxiv2022

Phenotypic and transcriptional response of Daphnia pulicaria to the combined effects of temperature and predation

Daphnia, an ecologically important zooplankton species in lakes, shows both genetic adaptation and phenotypic plasticity in response to temperature and fish predation, but little is known about the molecular basis of these responses and their potential interactions. We performed a factorial experiment exposing laboratory-propagated Daphnia pulicaria clones from two lakes in the Sierra Nevada mountains of California to normal or high temperature (15{degrees}C or 25{degrees}C) in the presence or absence of fish kairomones, then measured changes in life history and gene expression. Exposure to kairomones increased upper thermal tolerance limits for physiological activity in both clones. Cloned individuals matured at a younger age in response to higher temperature and kairomones, while size at maturity, fecundity and population intrinsic growth were only affected by temperature. At the molecular level, both clones expressed more genes differently in response to temperature than predation, but specific genes involved in metabolic, cellular, and genetic processes responded differently between the two clones. Although gene expression differed more between clones from different lakes than experimental treatments, similar phenotypic responses to predation risk and warming arose from these clone-specific patterns. Our results suggest that phenotypic plasticity responses to temperature and kairomones interact synergistically, with exposure to fish predators increasing the tolerance of Daphnia pulicaria to stressful temperatures, and that similar phenotypic responses to temperature and predator cues can be produced by divergent patterns of gene regulation.

ecology↗

bioRxiv2021

Polyclonal pathogen populations accelerate the evolution of antibiotic resistance in patients

Antibiotic resistance poses a global health threat, but the within-host drivers of resistance remain poorly understood. Pathogen populations are often assumed to be clonal within hosts, and resistance is thought to emerge due to selection for de novo variants. Here we show that pulmonary populations of the opportunistic pathogen P. aeruginosa are often polyclonal. Crucially, resistance evolves rapidly in patients colonized by polyclonal populations through selection for pre-existing resistant strains. In contrast, resistance evolves sporadically in patients colonized by monoclonal populations due to selection for novel resistance mutations. However, strong trade-offs between resistance and fitness occur in polyclonal populations that can drive the loss of resistant strains. In summary, we show that the within-host diversity of pathogen populations plays a key role in shaping the emergence of resistance in response to treatment. One sentence summaryAntibiotic resistance evolves quickly in patients colonized by polyclonal pathogen populations.

evolutionary biology↗

bioRxiv2021

Whole genome sequencing evidences higher rates of relapse in Clostridioides difficile infection caused by PCR ribotype 106

Increasing prevalence and widespread of Clostridioides difficile infection (CDI) caused by the epidemic DH/NAP11/106/ST-42 has been observed worldwide, probably fostered by its great capacity to produce spores or the higher resistance rates found in some strains. Previous studies have also attributed higher recurrence rates to RT106 as compared to others. This study describes the genetic analysis by whole genome sequencing (WGS) of primary and recurrent isolates of RT106 to determine if the higher rate of recurrence associated to RT106 is due to relapses, caused by the same strain, or reinfections, caused by different strains. The whole-genome sequences of ten primaries and fourteen recurrent RT106 isolates from ten patients were obtained to determine MLST profiles, resistance mutations and phylogenetic relatedness between the different isolates by comparative single nucleotide variants (SNV) analysis using the C. difficile DH/NAP11/106/ST-42 genome as reference (GenBank accession: GCA_002234355.1). All isolates were classified as ST42 and SNVs comparative analysis showed that those belonging to the same patient were isogenic (differed by [≤]3 SNVs), with one exception (6 SNVs); while strains belonging to different patients were not (differing by 4 to 43 SNVs) with two exceptions of isogenic isolates from different patients, suggesting putative transmission events. Phylogenetic analysis suggested the presence of similar local epidemic lineages, except for one patient whose isolates clustered with different US isolates. All the isolates, except those clustering with the US lineage, were also associated to moxifloxacin resistant since all of them were resistant by agar diffusion (MIC >32) and contained the Thr82Ile mutation in gyrA. Our results evidence that recurrent Clostridioides difficile infections caused by RT06/ST42 are mainly due to relapses, caused by primary strains, showing the great capacity of RT106/ST42 to persist and cause recurrences as compared to other ribotypes.

microbiology↗

bioRxiv2021

CK2 phosphorylation of human papillomavirus 16 E2 on serine 23 promotes interaction with TopBP1 and is critical for E2 plasmid retention function

During the human papillomavirus 16 (HPV16) life cycle, the E2 protein interacts with host factors to regulate viral transcription, replication and genome segregation/retention. Our understanding of host partner proteins and their roles in E2 functions remains incomplete. Here, we demonstrate that CK2 phosphorylation of E2 on serine 23 promotes interaction with TopBP1 in vitro and in vivo, and that E2 is phosphorylated on this residue during the HPV16 life cycle. We investigated the consequences of mutating serine 23 on E2 functions. E2-S23A activates and represses transcription identically to E2-WT (wild-type), and E2-S23A is as efficient as E2-WT in transient replication assays. However, E2-S23A has compromised interaction with mitotic chromatin when compared with E2-WT. In E2-WT cells, both E2 and TopBP1 levels increase during mitosis when compared with vector control cells. In E2-S23A cells, neither E2 nor TopBP1 levels increase during mitosis. We next tested whether this difference in E2-S23A levels during mitosis disrupts E2 plasmid retention function. We developed a novel plasmid retention assay and demonstrate that E2-S23A is deficient in plasmid retention when compared with E2-WT. siRNA targeted knockdown of TopBP1 abrogates E2-WT plasmid retention function. Introduction of the S23A mutation into the HPV16 genome resulted in delayed immortalization of human foreskin keratinocytes (HFK) and higher episomal viral genome copy number in resulting established HFK. Overall, our results demonstrate that CK2 phosphorylation of E2 on serine 23 promotes interaction with TopBP1, which is critical for E2 plasmid retention function and in HPV16 immortalization of keratinocytes. ImportanceHuman papillomaviruses are causative agents in around 5% of all cancers, with no specific anti-viral therapeutics available for treating infections or resultant cancers. In this report, we demonstrate that phosphorylation of HPV16 E2 by CK2 promotes formation of a complex formation with the cellular protein TopBP1 in vitro and in vivo. This complex results in stabilization of E2 during mitosis and mediates plasmid retention by E2. This function promotes the partitioning of viral genomes into the nuclei of daughter cells following mitosis. We demonstrate that CK2 phosphorylates E2 on serine 23 in vivo, and that CK2 inhibitors disrupt the E2-TopBP1 complex. Mutation of E2 serine 23 to alanine disrupts the HPV16 life cycle, demonstrating a critical function for this residue. Together, our results suggest that CK2 inhibitors may disrupt the E2-TopBP1 dependent HPV16 life cycle and potentially kill HPV16 positive cancers, which lays a molecular foundation to develop novel therapeutic approaches for combating HPV16 disease.

molecular biology↗

bioRxiv2021

Nse5/6 is a negative regulator of the ATPase activity of the Smc5/6 complex

The multi-component Smc5/6 complex plays a critical role in the resolution of recombination intermediates formed during mitosis and meiosis, and in the cellular response to replication stress. Using recombinant proteins, we have reconstituted a series of defined S. cerevisiae SMC5/6 complexes, visualised them by negative stain electron microscopy, and tested their ability to function as an ATPase. We find that only the six protein holo-complex is capable of turning over ATP and that its activity is significantly increased by the addition of double-stranded DNA to reaction mixes. Furthermore, stimulation is wholly dependent on functional ATP-binding pockets in both Smc5 and Smc6. Importantly, we demonstrate that budding yeast Nse5/6 acts as a negative regulator of Smc5/6 ATPase activity, binding to the head-end of the complex to suppress turnover, irrespective of the DNA-bound status of the complex.

biochemistry↗

bioRxiv2021

High fiber, whole foods dietary intervention alters the human gut microbiome but not fecal short-chain fatty acids

Dietary shifts can have a direct impact on the gut microbiome by preferentially selecting for microbes capable of utilizing the various dietary nutrients. Intake of dietary fiber has decreased precipitously in the last century, while consumption of processed foods has increased. Fiber, or microbiota-accessible carbohydrates (MACs), persist in the digestive tract and can be metabolized by specific bacteria encoding fiber degrading enzymes. Digestion of MACs results in the accumulation of short-chain fatty acids (SCFAs) and other metabolic byproducts that are critical to human health. Here, we implemented a two-week dietary fiber intervention aiming for 40-50 grams of fiber per day within the context of a course-based undergraduate research experience (CURE) (n = 20). By coupling shotgun metagenomic sequencing and targeted gas-chromatography mass spectrometry (GC/MS), we found that the dietary intervention significantly altered the composition of individual gut microbiomes, accounting for 8.3% of the longitudinal variability within subjects. Notably, microbial taxa that increased in relative abundance as a result of the diet change included known MAC degraders (i.e., Bifidobacterium and Lactobacillus). We further assessed the genetic diversity within Bifidobacterium, assayed by amplification of the groEL gene. Concomitant with microbial composition changes, we show an increase in the abundance of genes involved in inositol degradation. Despite these changes in gut microbiome composition, we did not detect a consistent shift in SCFA abundance. Collectively, our results demonstrate that on a short-term timescale of two weeks, increased fiber intake can induce compositional changes of the gut microbiome, including an increase in MAC degrading bacteria. IMPORTANCEA profound decrease in the consumption of dietary fiber in many parts of the world in the last century may be associated with the increasing prevalence of Type II diabetes, colon cancer, and other health problems. A typical U.S. diet includes about [~]15 grams of fiber per day, far less fiber than daily recommended allowance. Changes in dietary fiber intake affect human health not only through the uptake of nutrients directly, but also indirectly through changes in the microbial community and their associated metabolism. Here we conducted a two-week diet intervention in healthy young adults to investigate the impact of fiber consumption on the gut microbiome. Participants increased their average fiber consumption by 25 grams/day on average for two weeks. The high fiber diet intervention altered the gut microbiome of the study participants, including increases in known fiber degrading microbes such as Bifidobacterium and Lactobacillus.

microbiology↗

bioRxiv2020

Comparing Fecal, Saliva, and Chicha Microbiomes Between Mothers and Children in an Indigenous Ecuadorian Cohort

Recent research has elucidated many factors which play a role in the development and composition of human microbiomes. In this study we briefly examine the microbiomes of saliva and fecal samples from 71 indigenous individuals, and chicha samples from 28 single family households in a remote community in the Ecuadorian Amazon. Fecal and saliva samples were collected at two separate time points whereas chicha samples were collected at four time points, once each day of the fermentation process. In total 324 samples were collected: 113 saliva, 108 chicha, and 103 fecal. Microbial composition and diversity were assessed using shotgun metagenome sequence data. Chicha samples were found to be nearly entirely composed of the order Lactobacillales, accounting for 90.1% of the relative abundance. Saliva samples also contained a high relative abundance of Lactobacillales (31.9%) as well as being composed of Neisseriales (12.8%), Actinomycineae (8.7%), Bacteroidales (7.0%), Clostridiales (6.8%), Micrococcineae (6.5%), and Pasteurellales (6.0%). Fecal samples were largely composed of the three orders Clostridiales (33.7%), Bacteroidales (21.9%), and Bifidobacteriales (16.5%). Comparison of -diversity, as calculated by Shannons Diversity Index, in mothers and their offspring showed no significant difference between the two groups in either fecal or saliva samples. Comparison of {beta}-diversity in fecal and saliva samples, as calculated by the Bray-Curtis Dissimilarity measure, within household units and between differing households showed that members of the same household were significantly less dissimilar to each other than to members of other households in the community. Average microbiome composition for individuals within fecal and saliva samples was assessed to determine the impact of an individuals household on the composition of their microbiome. Household was determined to have a significant impact on both fecal and oral microbiome compositions.

microbiology↗

bioRxiv2020

Rapid evolution drives the rise and fall of carbapenem resistance during an acute Pseudomonas aeruginosa infection

It is well established that antibiotic treatment selects for resistance in pathogenic bacteria. However, the evolutionary responses of pathogen populations to antibiotic treatment during infections remain poorly resolved, especially in acute infections. Here we map the evolutionary responses to treatment in high definition through genomic and phenotypic characterization of >100 isolates from a patient with P. aeruginosa pneumonia. Antibiotic therapy (meropenem, colistin) caused a rapid crash of the P. aeruginosa population in the lung, but this decline was followed by the spread of meropenem resistance mutations that restrict antibiotic uptake (oprD) or modify LPS biosynthesis (wbpM). Low fitness strains with high-level meropenem resistance (oprD) were then replaced by high fitness strains with anti-resistance mutations in the MexAB-OprM efflux pump, causing a rapid decline in resistance to both meropenem and a collateral loss of resistance to a broad spectrum of antibiotics. In contrast, we did not observe any evolutionary responses to antibiotic treatment in the intestinal population of P. aeruginosa. Carbapenem antibiotics are key to the treatment of infections caused by Gram negative pathogens, and our work highlights the ability of natural selection to drive both the rapid rise and fall of carbapenem resistance during acute infections.

evolutionary biology↗

bioRxiv2020

A Genome-based Model to Predict the Virulence of Pseudomonas aeruginosa Isolates

Variation in the genome of Pseudomonas aeruginosa, an important pathogen, can have dramatic impacts on the bacteriums ability to cause disease. We therefore asked whether it was possible to predict the virulence of P. aeruginosa isolates based upon their genomic content. We applied a machine learning approach to a genetically and phenotypically diverse collection of 115 clinical P. aeruginosa isolates using genomic information and corresponding virulence phenotypes in a mouse model of bacteremia. We defined the accessory genome of these isolates through the presence or absence of accessory genomic elements (AGEs), sequences present in some strains but not others. Machine learning models trained using AGEs were predictive of virulence, with a mean nested cross-validation accuracy of 75% using the random forest algorithm. However, individual AGEs did not have a large influence on the algorithms performance, suggesting instead that the virulence prediction derives from a diffuse genomic signature. These results were validated with an independent test set of 25 P. aeruginosa isolates whose virulence was predicted with 72% accuracy. Machine learning models trained using core genome single nucleotide variants and whole genome k-mers also predicted virulence. Our findings are a proof of concept for the use of bacterial genomes to predict pathogenicity in P. aeruginosa and highlight the potential of this approach for predicting patient outcomes. IMPORTANCEPseudomonas aeruginosa is a clinically important gram-negative opportunistic pathogen. As a species, P. aeruginosa has a large degree of heterogeneity both through variation in sequences found throughout the species (core genome) and the presence or absence of sequences in different isolates (accessory genome). P. aeruginosa isolates also differ markedly in their ability to cause disease. In this study, we used machine learning to predict the virulence level of P. aeruginosa isolates in a mouse bacteremia model based on genomic content. We show that both the accessory and core genome are predictive of virulence. This study provides a machine learning framework to investigate relationships between bacterial genomes and complex phenotypes such as virulence.

genomics↗

bioRxiv2020

Evaluating rehabilitation progress using motion features identified by machine learning

Evaluating progress throughout a patients rehabilitation episode is critical for determining effectiveness of the selected treatments and contributing to the evidence-based practice. The evaluation process is complex due to the inherent large human variations in motor recovery and the limitations of commonly used clinical measurement tools. Information recorded during a robot-assisted rehabilitation process can provide an effective means to continuously quantitatively assess movement performance and rehabilitation progress. However, selecting appropriate motion features for rehabilitation evaluation has always been challenging. This paper exploits unsupervised feature learning techniques to reduce the complexity of building the evaluation model of patients progress. A new feature learning technique is developed to select the most significant features from a large amount of kinematic features measured from robotics, providing clinically useful information to health practitioners with reduction of modeling complexity. A novel indicator that can reflect monotonicity and trendability is proposed to evaluate the suitability of kinematic features, which are derived from the collected data of a population of stroke patients participating in robot-aided rehabilitation. The selected kinematic features allow for human variations across a population of patients as well as over the sequence of rehabilitation sessions. The study is based on data records pertaining to 41 stroke patients using three different robot assisted exercises for upper limb rehabilitation. Consistent with the literature, the results indicate that features based on movement smoothness are the best measures among 17 kinematic features used to evaluate rehabilitation progress.

bioengineering↗

bioRxiv2019

Cervicovaginal microbiome composition drives metabolic profiles in healthy pregnancy

BackgroundMicrobes and their metabolic products influence early-life immune and microbiome development, yet remain understudied during pregnancy. Vaginal microbial communities are typically dominated by one or a few well adapted microbes, which are able to survive in a narrow pH range. In comparison to other human-associated microbes, vaginal microbes are adapted to live on host-derived carbon sources, likely sourced from glycogen and mucin present in the vaginal environment. MethodsUsing 16S rRNA and ITS amplicon sequencing, we characterized the cervicovaginal microbiomes of 18 healthy women throughout the three trimesters of pregnancy. Shotgun metagenomic sequencing permitted refinement of the taxonomy established by amplicon sequencing, and identification of functional genes. Additionally, we analyzed saliva and urine metabolomes using GC-TOF and LC-MS/MS lipidomics approaches for samples from mothers and their infants through the first year of life. ResultsAmplicon sequencing revealed most women had either a simple community with one highly abundant species of Lactobacillus or a more diverse community characterized by a high abundance of Gardnerella, as has also been previously described in several independent cohorts. Integrating GC-TOF and lipidomics data with amplicon sequencing, we found metabolites that distinctly associate with particular communities. For example, cervicovaginal microbial communities dominated by Lactobacillus crispatus also have high mannitol levels, which contradicts the basic characterization of L. crispatus as a homofermentative Lactobacillus species. It may be that fluctuations in which Lactobacillus dominate a particular vaginal microbiome are dictated by the availability of host sugars, such as fructose, which is the most likely substrate being converted to mannitol. Furthermore, indole-3-lactate (ILA) was also indicative of L. crispatus specifically. ILA has immunomodulatory properties through binding the human aryl hydrocarbon receptor (AhR), which may maintain the especially low diversity of L. crispatus dominated communities. ConclusionsOverall, using a multi- omic approach, we begin to address the genetic and molecular means by which a particular vaginal microbiome becomes vulnerable to large changes in composition.

microbiology↗

bioRxiv2019

A role of the Nse4 kleisin and Nse1/Nse3 KITE subunits in the ATPase cycle of SMC5/6

The SMC (Structural Maintenance of Chromosomes) complexes are composed of SMC dimers, kleisin and kleisin-interacting subunits. Mutual interactions of these subunits constitute the basal architecture of the SMC complexes. Particularly, terminal domains of the kleisin subunit bridge the SMC head domains of the SMC molecules. Binding of ATP molecules to the heads and their hydrolysis alter the shape of long SMC molecules (from rod-like to open-ring shapes) and power them with motor activity. The kleisin-interacting (HAWK or KITE) subunits bind kleisin linker regions and regulate such dynamic activities.\n\nWe developed new systems to follow the interactions between SMC5/6 subunits and stability of the SMC5/6 complexes. First, we show that the N-terminal domain of the Nse4 kleisin molecule binds to the SMC6 neck and bridges it to the SMC5 head. Second, binding of the Nse1 and Nse3 KITE proteins to the Nse4 linker part increases stability of the ATP-free SMC5/6 complex. In contrast, binding of ATP to the SMC5/6 complex containing KITE subunits significantly decreases its stability. Elongation of the Nse4 linker partially suppresses instability of the ATP-bound complex, suggesting that the binding of the KITE proteins to the Nse4 linker constrains its limited size. Our data suggest that the KITE proteins may shape the Nse4 linker to fit the ATP-free complex optimally and to facilitate opening of the complex upon ATP binding. This mechanism suggests an important role of the KITE subunits in the dynamics of the SMC5/6 complexes.\n\nAUTHOR SUMMARYThe SMC5/6 complex is member of the Structural maintenance of chromosomes (SMC) family, key organizers of both prokaryotic and eukaryotic genomes. Their architecture and dynamics (driven by ATP binding and hydrolysis) are essential for cellular processes, like chromatin segregation, condensation, replication and repair. In this paper, we described conserved mode of the Nse4 kleisin subunit binding to the SMC6 (similar to cohesin and condensin) and its bridging role. Furthermore, we showed different impact of the binding of the Nse1-Nse3 KITE subunits to the Nse4 kleisin bridge. Our study suggested that the KITE proteins modulate the stability of the SMC5/6 complex, depending on its binding and hydrolysis of ATP. Our findings uncover molecular mechanisms underlying dynamics of the SMC5/6 complexes.

genetics↗

bioRxiv2019

In vitro and in vivo efficacy of the combination of colistin and endolysins against clinical strains of Multi-Drug Resistant (MDR) pathogens

The multidrug resistance (MDR) among pathogenic bacteria is jeopardizing the worth of antimicrobials, which had previously changed medical sciences. In this study, we used bioinformatic tools to identify the endolysins ElyA1 and ElyA2 (GH108-PG3 family) present in the genome of bacteriophages Ab1051{Phi} and Ab1052{Phi}, respectively. The muralytic activity of these endolysins over MDR clinical isolates (Acinetobacter baumannii, Pseudomonas aeruginosa and Klebsiella pneumoniae) was tested using the turbidity reduction assay. The minimal inhibitory concentrations (MICs) of endolysin, colistin and their combination were determined using the microdilution checkerboard method. The antimicrobial activity of the combinations was confirmed by time kill curves and in vivo assays in larvae of Galleria mellonella. Our results showed that ElyA1 displayed activity against all 25 strains of A. baumannii and P. aeruginosa tested and against 13 out of 17 strains of K. pneumoniae. No activity was detected when assays were done with endolysin ElyA2. The combined antimicrobial activity of colistin and endolysin ElyA1 yielded a reduction in the colistin MIC for all strains studied, except K. pneumoniae. These results were confirmed in vivo in G. mellonella survival assays. In conclusion, the combination of colistin with new endolysins such as ElyA1 could increase the bactericidal activity and reduce the MIC of the antibiotic, thus also reducing the associated toxicity.\n\nIMPORTANCEThe development of multiresistance by pathogen bacteria increases the necessity of the development of new antimicrobial strategies. In this work, we combined the effect of the colistin with a new endolysin, ElyA1, from a bacteriophage present in the clinical strain of Acinetobacter baumannii Ab105. ElyA1 is a lysozyme-like family (GH108-GP3), whose antimicrobial activity was described for first time in this work. Also, another endolysin, ElyA2, with the same origin and family, was characterized but in this case no activity was detected. ElyA1 presented lytic activity over a broad spectrum of strains from A. baumannii, Pseudomonas aeruginosa, and Klebsiella pneumoniae. When colistin was combined with ElyA1 an increase of the antimicrobial activity was observed with a reduced concentration of colistin, and this observation was also confirmed in vivo in Galleria mellonella larvae. The combination of colistin with new endolysins as ElyA1 could increase the bactericidal activity and lowering the MIC of the antibiotic, thus also reducing the associated toxicity.

microbiology↗

bioRxiv2019

Fighting antimicrobial resistance in Pseudomonas aeruginosa with machine learning-enabled molecular diagnostics

The growing importance of antibiotic resistance on clinical outcomes and cost of care underscores the need for optimization of current diagnostics. For a number of bacterial species antimicrobial resistance can be unambiguously predicted based on their genome sequence. In this study, we sequenced the genomes and transcriptomes of 414 drug-resistant clinical Pseudomonas aeruginosa isolates. By training machine learning classifiers on information about the presence or absence of genes, their sequence variation, and gene expression profiles, we generated predictive models and identified biomarkers of susceptibility or resistance to four commonly administered antimicrobial drugs. Using these data types alone or in combination resulted in high (0.8-0.9) or very high (>0.9) sensitivity and predictive values, where the relative contribution of the different categories of biomarkers strongly depended on the antibiotic. For all drugs except for ciprofloxacin, gene expression information substantially improved diagnostic performance. Our results pave the way for the development of a molecular resistance profiling tool that reliably predicts antimicrobial susceptibility based on genomic and transcriptomic markers. The implementation of a molecular susceptibility test system in routine clinical microbiology diagnostics holds promise to provide earlier and more detailed information on antibiotic resistance profiles of bacterial pathogens and thus could change how physicians treat bacterial infections.

microbiology↗