2023 Neer Award for Basic Science: Genetics of Cutibacterium acnes in Revision Shoulder Arthroplasty: A Large-Scale Bacterial Whole-Genome Sequencing Study.

BACKGROUND: Cutibacterium acnes is the bacterium most commonly responsible for shoulder periprosthetic joint infection (PJI) and is often cultured from samples obtained at the time of revision for failed shoulder arthroplasty. We sought to determine whether these bacteria originate from the patient or from exogenous sources. We also sought to identify which C. acnes genetic traits were associated with the development of shoulder PJI. METHODS: We performed bacterial whole-genome sequencing of C. acnes from a single-institution repository of cultures obtained before or during primary and revision shoulder arthroplasty and correlated the molecular epidemiology and genetic content of strains with clinical features of infection. RESULTS: A total of 341 isolates collected over a four-year period from 88 patients were sequenced. C. acnes cultured from surgical specimens demonstrated significant similarity to the strains colonizing the skin of the same patient (p<0.001). Infrequently, there was evidence of strains shared across unrelated patients, suggesting that exogenous sources of C. acnes culture-positivity were uncommon. Phylotypes IB and II were modestly associated with clinical features of PJI, but all phylotypes appeared inherently capable of causing disease. Chronic shoulder PJI was associated with the absence of common C. acnes genes involved in bacterial quorum-sensing (luxS, tqsA). CONCLUSION: C. acnes strains cultured from deep intraoperative sources during revision shoulder arthroplasty demonstrate strong genetic similarity to the strains colonizing a patient's skin. Some phylotypes of C. acnes commonly colonizing human skin are modestly more virulent than others, but all phylotypes have a capacity for PJI. C. acnes cultured from cases of PJI commonly demonstrated genetic hallmarks associated with adaptation from acute to chronic phases of infection. This is the strongest evidence to date supporting the role of the patient's own, cutaneous C. acnes strains in the pathogenesis of shoulder arthroplasty infection. Our findings support the importance of further research focused on perioperative decolonization and management of endogenous bacteria that are likely to be introduced into the arthroplasty wound at the time of skin incision.

Contribution of the patient microbiome to surgical site infection and antibiotic prophylaxis failure in spine surgery.

Despite modern antiseptic techniques, surgical site infection (SSI) remains a leading complication of surgery. However, the origins of SSI and the high rates of antimicrobial resistance observed in these infections are poorly understood. Using instrumented spine surgery as a model of clean (class I) skin incision, we prospectively sampled preoperative microbiomes and postoperative SSI isolates in a cohort of 204 patients. Combining multiple forms of genomic analysis, we correlated the identity, anatomic distribution, and antimicrobial resistance profiles of SSI pathogens with those of preoperative strains obtained from the patient skin microbiome. We found that 86% of SSIs, comprising a broad range of bacterial species, originated endogenously from preoperative strains, with no evidence of common source infection among a superset of 1610 patients. Most SSI isolates (59%) were resistant to the prophylactic antibiotic administered during surgery, and their resistance phenotypes correlated with the patient's preoperative resistome (P = 0.0002). These findings indicate the need for SSI prevention strategies tailored to the preoperative microbiome and resistome present in individual patients.

Longitudinal profiling of the intestinal microbiome in children with cystic fibrosis treated with elexacaftor-tezacaftor-ivacaftor.

The intestinal microbiome influences growth and disease progression in children with cystic fibrosis (CF). Elexacaftor-tezacaftor-ivacaftor (ELX/TEZ/IVA), the newest pharmaceutical modulator for CF, restores the function of the pathogenic mutated CF transmembrane conductance regulator (CFTR) channel. We performed a single-center longitudinal analysis of the effect of ELX/TEZ/IVA on the intestinal microbiome, intestinal inflammation, and clinical parameters in children with CF. Following ELX/TEZ/IVA, children with CF had significant improvements in body mass index and percent predicted forced expiratory volume in one second, and required fewer antibiotics for respiratory infections. Intestinal microbiome diversity increased following ELX/TEZ/IVA coupled with a decrease in the intestinal carriage of Staphylococcus aureus, the predominant respiratory pathogen in children with CF. There was a reduced abundance of microbiome-encoded antibiotic resistance genes. Microbial pathways for aerobic respiration were reduced after ELX/TEZ/IVA. The abundance of microbial acid tolerance genes was reduced, indicating microbial adaptation to increased CFTR function. In all, this study represents the first comprehensive analysis of the intestinal microbiome in children with CF receiving ELX/TEZ/IVA.IMPORTANCECystic fibrosis (CF) is an autosomal recessive disease with significant gastrointestinal symptoms in addition to pulmonary complications. Recently approved treatments for CF, CF transmembrane conductance regulator (CFTR) modulators, are anticipated to substantially improve the care of people with CF and extend their lifespans. Prior work has shown that the intestinal microbiome correlates with health outcomes in CF, particularly in children. Here, we study the intestinal microbiome of children with CF before and after the CFTR modulator, ELX/TEZ/IVA. We identify promising improvements in microbiome diversity, reduced measures of intestinal inflammation, and reduced antibiotic resistance genes. We present specific bacterial taxa and protein groups which change following ELX/TEZ/IVA. These results will inform future mechanistic studies to understand the microbial improvements associated with CFTR modulator treatment. This study demonstrates how the microbiome can change in response to a targeted medication that corrects a genetic disease.

Transposon sequencing identifies genes impacting Staphylococcus aureus invasion in a human macrophage model.

Staphylococcus aureus is a facultative intracellular pathogen in many host cell types, facilitating its persistence in chronic infections. The genes contributing to intracellular pathogenesis have not yet been fully enumerated. Here, we cataloged genes influencing S. aureus invasion and survival within human THP-1 derived macrophages using two laboratory strains (ATCC2913 and JE2). We developed an in vitro transposition method to produce highly saturated transposon mutant libraries in S. aureus and performed transposon insertion sequencing (Tn-Seq) to identify candidate genes with significantly altered abundance following macrophage invasion. While some significant genes were strain-specific, 108 were identified as common across both S. aureus strains, with most (n = 106) being required for optimal macrophage infection. We used CRISPR interference (CRISPRi) to functionally validate phenotypic contributions for a subset of genes. Of the 20 genes passing validation, seven had previously identified roles in S. aureus virulence, and 13 were newly implicated. Validated genes frequently evidenced strain-specific effects, yielding opposing phenotypes when knocked down in the alternative strain. Genomic analysis of de novo mutations occurring in groups (n = 237) of clonally related S. aureus isolates from the airways of chronically infected individuals with cystic fibrosis (CF) revealed significantly greater in vivo purifying selection in conditionally essential candidate genes than those not associated with macrophage invasion. This study implicates a core set of genes necessary to support macrophage invasion by S. aureus, highlights strain-specific differences in phenotypic effects of effector genes, and provides evidence for selection of candidate genes identified by Tn-Seq analyses during chronic airway infection in CF patients in vivo.

Longitudinal Profiling of the Intestinal Microbiome in Children with Cystic Fibrosis Treated with Elexacaftor-Tezacaftor-Ivacaftor.

The intestinal microbiome influences growth and disease progression in children with cystic fibrosis (CF). Elexacaftor-tezacaftor-ivacaftor (ELX/TEZ/IVA), the newest pharmaceutical modulator for CF, restores function of the pathogenic mutated CFTR channel. We performed a single-center longitudinal analysis of the effect of ELX/TEZ/IVA on the intestinal microbiome, intestinal inflammation, and clinical parameters in children with CF. Following ELX/TEZ/IVA, children with CF had significant improvements in BMI, ppFEV1 and required fewer antibiotics for respiratory infections. Intestinal microbiome diversity increased following ELX/TEZ/IVA coupled with a decrease in the intestinal carriage of Staphylococcus aureus, the predominant respiratory pathogen in children with CF. There was a reduced abundance of microbiome-encoded antibiotic-resistance genes. Microbial pathways for aerobic respiration were reduced after ELX/TEZ/IVA. The abundance of microbial acid tolerance genes was reduced, indicating microbial adaptation to increased CFTR function. In all, this study represents the first comprehensive analysis of the intestinal microbiome in children with CF receiving ELX/TEZ/IVA.

In Vitro Selection Identifies Staphylococcus aureus Genes Influencing Biofilm Formation.

Staphylococcus aureus generates biofilms during many chronic human infections, which contributes to its growth and persistence in the host. Multiple genes and pathways necessary for S. aureus biofilm production have been identified, but knowledge is incomplete, and little is known about spontaneous mutations that increase biofilm formation as infection progresses. Here, we performed in vitro selection of four S. aureus laboratory strains (ATCC 29213, JE2, N315, and Newman) to identify mutations associated with enhanced biofilm production. Biofilm formation increased in passaged isolates from all strains, exhibiting from 1.2- to 5-fold the capacity of parental lines. Whole-genome sequencing identified nonsynonymous mutations affecting 23 candidate genes and a genomic duplication encompassing sigB. Six candidate genes significantly impacted biofilm formation as isogenic transposon knockouts: three were previously reported to impact S. aureus biofilm formation (icaR, spdC, and codY), while the remaining three (manA, narH, and fruB) were newly implicated by this study. Plasmid-mediated genetic complementation of manA, narH, and fruB transposon mutants corrected biofilm deficiencies, with high-level expression of manA and fruB further enhancing biofilm formation over basal levels. This work recognizes genes not previously identified as contributing to biofilm formation in S. aureus and reveals genetic changes able to augment biofilm production by that organism.

Genome Capture Sequencing Selectively Enriches Bacterial DNA and Enables Genome-Wide Measurement of Intrastrain Genetic Diversity in Human Infections.

Within-host evolution produces genetic diversity in bacterial strains that cause chronic human infections. However, the lack of facile methods to measure bacterial allelic variation in clinical samples has limited understanding of intrastrain diversity's effects on disease. Here, we report a new method termed genome capture sequencing (GenCap-Seq) in which users inexpensively make hybridization probes from genomic DNA or PCR amplicons to selectively enrich and sequence targeted bacterial DNA from clinical samples containing abundant human or nontarget bacterial DNA. GenCap-Seq enables accurate measurement of allele frequencies over targeted regions and is scalable from specific genes to entire genomes, including the strain-specific accessory genome. The method is effective with samples in which target DNA is rare and inhibitory and DNA-degrading substances are abundant, including human sputum and feces. In proof-of-principle experiments, we used GenCap-Seq to investigate the responses of diversified Pseudomonas aeruginosa populations chronically infecting the lungs of people with cystic fibrosis to in vivo antibiotic exposure, and we found that treatment consistently reduced intrastrain genomic diversity. In addition, analysis of gene-level allele frequency changes suggested that some genes without conventional resistance functions may be important for bacterial fitness during in vivo antibiotic exposure. GenCap-Seq's ability to scalably enrich targeted bacterial DNA from complex samples will enable studies on the effects of intrastrain and intraspecies diversity in human infectious disease. IMPORTANCE Genetic diversity evolves in bacterial strains during human infections and could affect disease manifestations and treatment resistance. However, the extent of diversity present in vivo and its changes over time are difficult to measure by conventional methods. We developed a novel approach, GenCap-Seq, to enrich microbial DNA from complex human samples like sputum and feces for genome-wide measurements of bacterial allelic diversity. The approach is inexpensive, scalable to encompass entire targeted genomes, and works in the presence of abundant untargeted nucleic acids and inhibiting substances. We used GenCap-Seq to investigate in vivo responses of diversified bacterial strains to antibiotic treatment. This method will enable new ideas about the effects of intrastrain diversity on human infections to be tested.

Ultrasensitive Quantitation of Genomic Chimerism by Single-Molecule Molecular Inversion Probe Capture and High-Throughput Sequencing of Copy Number Deletion Polymorphisms.

Genomic chimerism represents co-existing cells with different genotypes and has diagnostic significance in transplant engraftment monitoring, residual cancer detection, and other contexts. We previously described an approach to chimerism detection by interrogating variably present or absent genomic loci using single-molecule molecular inversion probes (smMIPs) and next-generation sequencing, which provided ultrasensitive limits of detection (<1 in 10,000 cells) but was not reliably quantitative. Herein, smMIP testing was modified to accurately quantitate chimeric cells by incorporating copy number neutral control loci for data normalization and computationally modeling cell mixtures from individual-specific genotypes. Data demonstrate precision and accuracy over three orders of magnitude (0.01% to 50% chimerism). Seventy hematopoietic stem cell transplant specimens from single (n = 42) or double (n = 28) donors were evaluated, benchmarking smMIP against conventional variable number tandem repeat (VNTR) analysis and an unrelated, ultrasensitive polymorphism-specific quantitative PCR (PS-qPCR) assay. Quantitative concordance of all three assays was high (P < 0.0005, Pearson correlation coefficient), although smMIP correlated better with VNTR testing than PS-qPCR. smMIP and PS-qPCR collectively identified low-level chimerism in all specimens testing negative by VNTR (n = 41 and n = 45 of 48 specimens, respectively). This work demonstrates the feasibility of smMIP-based chimerism testing for quantitative and ultrasensitive measurement of genomic chimerism at practical levels approaching one in one million cells, and cross-validates the approach.

Repeated isolation of an antibiotic-dependent and temperature-sensitive mutant of Pseudomonas aeruginosa from a cystic fibrosis patient.

BACKGROUND: Bacteria adapt to survive and grow in different environments. Genetic mutations that promote bacterial survival under harsh conditions can also restrict growth. The causes and consequences of these adaptations have important implications for diagnosis, pathogenesis, and therapy. OBJECTIVES: We describe the isolation and characterization of an antibiotic-dependent, temperature-sensitive Pseudomonas aeruginosa mutant chronically infecting the respiratory tract of a cystic fibrosis (CF) patient, underscoring the clinical challenges bacterial adaptations can present. METHODS: Respiratory samples collected from a CF patient during routine care were cultured for standard pathogens. P. aeruginosa isolates recovered from samples were analysed for in vitro growth characteristics, antibiotic susceptibility, clonality, and membrane phospholipid and lipid A composition. Genetic mutations were identified by whole genome sequencing. RESULTS: P. aeruginosa isolates collected over 5 years from respiratory samples of a CF patient frequently harboured a mutation in phosphatidylserine decarboxylase (psd), encoding an enzyme responsible for phospholipid synthesis. This mutant could only grow at 37°C when in the presence of supplemented magnesium, glycerol, or, surprisingly, the antibiotic sulfamethoxazole, which the source patient had repeatedly received. Of concern, this mutant was not detectable on standard selective medium at 37°C. This growth defect correlated with alterations in membrane phospholipid and lipid A content. CONCLUSIONS: A P. aeruginosa mutant chronically infecting a CF patient exhibited dependence on sulphonamides and would likely evade detection using standard clinical laboratory methods. The diagnostic and therapeutic challenges presented by this mutant highlight the complex interplay between bacterial adaptation, antibiotics, and laboratory practices, during chronic bacterial infections.

Polyclonality, Shared Strains, and Convergent Evolution in Chronic Cystic Fibrosis Staphylococcus aureus Airway Infection.

Rationale:Staphylococcus aureus is the most common respiratory pathogen isolated from patients with cystic fibrosis (CF) in the United States. Although modes of acquisition and genetic adaptation have been described for Pseudomonas aeruginosa, resulting in improved diagnosis and treatment, these features remain more poorly defined for S. aureus.Objectives: To characterize the molecular epidemiology and genetic adaptation of S. aureus during chronic CF airway infection and in response to antibiotic therapy.Methods: We performed whole-genome sequencing of 1,382 S. aureus isolates collected longitudinally over a mean 2.2 years from 246 children with CF at five U.S. centers between 2008 and 2017. Results were integrated with clinical and demographic data to characterize bacterial population dynamics and identify common genetic targets of in vivo adaptation.Measurements and Main Results: Results showed that 45.5% of patients carried multiple, coexisting S. aureus lineages, often having different antibiotic susceptibility profiles. Adaptation during the course of infection commonly occurred in a set of genes related to persistence and antimicrobial resistance. Individual sequence types demonstrated wide geographic distribution, and we identified limited strain-sharing among children linked by common household or clinical exposures. Unlike P. aeruginosa, S. aureus genetic diversity was unconstrained, with an ongoing flow of new genetic elements into the population of isolates from children with CF.Conclusions: CF airways are frequently coinfected by multiple, genetically distinct S. aureus lineages, indicating that current clinical procedures for sampling isolates and selecting antibiotics are likely inadequate. Strains can be shared by patients in close domestic or clinical contact and can undergo convergent evolution in key persistence and antimicrobial-resistance genes, suggesting novel diagnostic and therapeutic approaches for future study.

Identifying Optimal Loci for the Molecular Diagnosis of Microsatellite Instability.

BACKGROUND: Microsatellite instability (MSI) predicts oncological response to checkpoint blockade immunotherapies. Although microsatellite mutation is pathognomonic for the condition, loci have unequal diagnostic value for predicting MSI within and across cancer types. METHODS: To better inform molecular diagnosis of MSI, we examined 9438 tumor-normal exome pairs and 901 whole genome sequence pairs from 32 different cancer types and cataloged genome-wide microsatellite instability events. Using a statistical framework, we identified microsatellite mutations that were predictive of MSI within and across cancer types. The diagnostic accuracy of different subsets of maximally informative markers was estimated computationally using a dedicated validation set. RESULTS: Twenty-five cancer types exhibited hypermutated states consistent with MSI. Recurrently mutated microsatellites associated with MSI were identifiable in 15 cancer types, but were largely specific to individual cancer types. Cancer-specific microsatellite panels of 1 to 7 loci were needed to attain ≥95% diagnostic sensitivity and specificity for 11 cancer types, and in 8 of the cancer types, 100% sensitivity and specificity were achieved. Breast cancer required 800 loci to achieve comparable performance. We were unable to identify recurrent microsatellite mutations supporting reliable MSI diagnosis in ovarian tumors. Features associated with informative microsatellites were cataloged. CONCLUSIONS: Most microsatellites informative for MSI are specific to particular cancer types, requiring the use of tissue-specific loci for optimal diagnosis. Limited numbers of markers are needed to provide accurate MSI diagnosis in most tumor types, but it is challenging to diagnose breast and ovarian cancers using predefined microsatellite locus panels.

Open-Sourced CIViC Annotation Pipeline to Identify and Annotate Clinically Relevant Variants Using Single-Molecule Molecular Inversion Probes.

PURPOSE: Clinical targeted sequencing panels are important for identifying actionable variants for patients with cancer; however, existing approaches do not provide transparent and rationally designed clinical panels to accommodate the rapidly growing knowledge within oncology. MATERIALS AND METHODS: We used the Clinical Interpretations of Variants in Cancer (CIViC) database to develop an Open-Sourced CIViC Annotation Pipeline (OpenCAP). OpenCAP provides methods to identify variants within the CIViC database, build probes for variant capture, use probes on prospective samples, and link somatic variants to CIViC clinical relevance statements. OpenCAP was tested using a single-molecule molecular inversion probe (smMIP) capture design on 27 cancer samples from 5 tumor types. In total, 2,027 smMIPs were designed to target 111 eligible CIViC variants (61.5 kb of genomic space). RESULTS: When compared with orthogonal sequencing, CIViC smMIP sequencing demonstrated a 95% sensitivity for variant detection (n = 61 of 64 variants). Variant allele frequencies for variants identified on both sequencing platforms were highly concordant (Pearson's r = 0.885; n = 61 variants). Moreover, for individuals with paired tumor and normal samples (n = 12), 182 clinically relevant variants missed by orthogonal sequencing were discovered by CIViC smMIP sequencing. CONCLUSION: The OpenCAP design paradigm demonstrates the utility of an open-source and open-access database built on attendant community contributions with peer-reviewed interpretations. Use of a public repository for variant identification, probe development, and variant interpretation provides a transparent approach to build dynamic next-generation sequencing-based oncology panels.

Genomic Analysis Identifies Novel Pseudomonas aeruginosa Resistance Genes under Selection during Inhaled Aztreonam Therapy In Vivo.

Inhaled aztreonam is increasingly used for chronic Pseudomonas aeruginosa suppression in patients with cystic fibrosis (CF), but the potential for that organism to evolve aztreonam resistance remains incompletely explored. Here, we performed genomic analysis of clonally related pre- and posttreatment CF clinical isolate pairs to identify genes that are under positive selection during aztreonam therapy in vivo We identified 16 frequently mutated genes associated with aztreonam resistance, the most prevalent being ftsI and ampC, and 13 of which increased aztreonam resistance when introduced as single gene transposon mutants. Several previously implicated aztreonam resistance genes were found to be under positive selection in clinical isolates even in the absence of inhaled aztreonam exposure, indicating that other selective pressures in the cystic fibrosis airway can promote aztreonam resistance. Given its potential to confer plasmid-mediated resistance, we further characterized mutant ampC alleles and performed artificial evolution of ampC for maximal activity against aztreonam. We found that naturally occurring ampC mutants conferred variably increased resistance to aztreonam (2- to 64-fold) and other ß-lactam agents but that its maximal evolutionary capacity for hydrolyzing aztreonam was considerably higher (512- to 1,024-fold increases) and was achieved while maintaining or increasing resistance to other drugs. These studies implicate novel chromosomal aztreonam resistance determinants while highlighting that different mutations are favored during selection in vivo and in vitro, show that ampC has a high maximal potential to hydrolyze aztreonam, and provide an approach to disambiguate mutations promoting specific resistance phenotypes from those more generally increasing bacterial fitness in vivo.

Accurate Pan-Cancer Molecular Diagnosis of Microsatellite Instability by Single-Molecule Molecular Inversion Probe Capture and High-Throughput Sequencing.

BACKGROUND: Microsatellite instability (MSI) is an emerging actionable phenotype in oncology that informs tumor response to immune checkpoint pathway immunotherapy. However, there remains a need for MSI diagnostics that are low cost, highly accurate, and generalizable across cancer types. We developed a method for targeted high-throughput sequencing of numerous microsatellite loci with pan-cancer informativity for MSI using single-molecule molecular inversion probes (smMIPs). METHODS: We designed a smMIP panel targeting 111 loci highly informative for MSI across cancers. We developed an analytical framework taking advantage of smMIP-mediated error correction to specifically and sensitively detect instability events without the need for typing matched normal material. RESULTS: Using synthetic DNA mixtures, smMIPs were sensitive to at least 1% MSI-positive cells and were highly consistent across replicates. The fraction of identified unstable microsatellites discriminated tumors exhibiting MSI from those lacking MSI with high accuracy across colorectal (100% diagnostic sensitivity and specificity), prostate (100% diagnostic sensitivity and specificity), and endometrial cancers (95.8% diagnostic sensitivity and 100% specificity). MSI-PCR, the current standard-of-care molecular diagnostic for MSI, proved equally robust for colorectal tumors but evidenced multiple false-negative results in prostate (81.8% diagnostic sensitivity and 100% specificity) and endometrial (75.0% diagnostic sensitivity and 100% specificity) tumors. CONCLUSIONS: smMIP capture provides an accurate, diagnostically sensitive, and economical means to diagnose MSI across cancer types without reliance on patient-matched normal material. The assay is readily scalable to large numbers of clinical samples, enables automated and quantitative analysis of microsatellite instability, and is readily standardized across clinical laboratories.

Ultrasensitive Detection of Chimerism by Single-Molecule Molecular Inversion Probe Capture and High-Throughput Sequencing of Copy Number Deletion Polymorphisms.

BACKGROUND: Genomic chimerism, the co-occurrence of cells from different genetic origins, provides important diagnostic information in diverse clinical contexts, including graft injury detection and longitudinal surveillance of hematopoietic stem cell transplantation patients, but existing assays are limiting. Here we applied single-molecule molecular inversion probes (smMIPs), a high-throughput sequencing technology combining multiplexed target capture with read quantification mediated by unique molecular identifiers, to detect chimerism based on the presence or absence of polymorphic genomic loci. METHODS: We designed a 159-smMIP panel targeting 40 autosomal regions of frequent homozygous deletion across human populations and 2 sex-linked loci. We developed methods for detecting and quantitating loci absent from 1 cell population but present in another, which could be used to sensitively identify chimeric cell populations. RESULTS: Unrelated individuals and first-degree relatives were highly polymorphic across the loci examined. Using synthetic DNA mixtures, limits of detection of at least 1 in 10000 chimeric cells were demonstrated without prior knowledge of genotypes, and mixtures of up to 4 separate donors could be deconvoluted. Quantitative linearity over 4 orders of magnitude and false-positive rates <1 in 85000 events were achieved. Eleven of 11 posttransplant clinical specimens from patients with hematological malignancies testing positive for residual cancer by conventional methods had detectable chimeric populations by smMIP, whereas 11 of 11 specimens testing negative by conventional methods were low-positive for chimerism by smMIP. CONCLUSIONS: smMIPs are scalable to high sensitivity and large numbers of informative markers, enabling ultrasensitive chimerism detection for many clinical purposes.

Evolved Aztreonam Resistance Is Multifactorial and Can Produce Hypervirulence in Pseudomonas aeruginosa.

While much attention has been focused on acquired antibiotic resistance genes, chromosomal mutations may be most important in chronic infections where isolated, persistently infecting lineages experience repeated antibiotic exposure. Here, we used experimental evolution and whole-genome sequencing to investigate chromosomally encoded mutations causing aztreonam resistance in Pseudomonas aeruginosa and characterized the secondary consequences of resistance development. We identified 19 recurrently mutated genes associated with aztreonam resistance. The most frequently observed mutations affected negative transcriptional regulators of the mexAB-oprM efflux system and the target of aztreonam, ftsI While individual mutations conferred modest resistance gains, high-level resistance (1,024 µg/ml) was achieved through the accumulation of multiple variants. Despite being largely stable when strains were passaged in the absence of antibiotics, aztreonam resistance was associated with decreased in vitro growth rates, indicating an associated fitness cost. In some instances, evolved aztreonam-resistant strains exhibited increased resistance to structurally unrelated antipseudomonal antibiotics. Surprisingly, strains carrying evolved mutations which affected negative regulators of mexAB-oprM (mexR and nalD) demonstrated enhanced virulence in a murine pneumonia infection model. Mutations in these genes, and other genes that we associated with aztreonam resistance, were common in P. aeruginosa isolates from chronically infected patients with cystic fibrosis. These findings illuminate mechanisms of P. aeruginosa aztreonam resistance and raise the possibility that antibiotic treatment could inadvertently select for hypervirulence phenotypes.IMPORTANCE Inhaled aztreonam is a relatively new antibiotic which is being increasingly used to treat cystic fibrosis patients with Pseudomonas aeruginosa airway infections. As for all antimicrobial agents, bacteria can evolve resistance that decreases the effectiveness of the drug; however, the mechanisms and consequences of aztreonam resistance are incompletely understood. Here, using experimental evolution, we have cataloged spontaneous mutations conferring aztreonam resistance and have explored their effects. We found that a diverse collection of genes contributes to aztreonam resistance, each with a small but cumulative effect. Surprisingly, we found that selection for aztreonam resistance mutations could confer increased resistance to other antibiotics and promote hypervirulence in a mouse infection model. Our study reveals inherent mechanisms of aztreonam resistance and indicates that aztreonam exposure can have unintended secondary effects.

Ultrasensitive detection of acute myeloid leukemia minimal residual disease using single molecule molecular inversion probes.

The identification of minimal residual disease is the primary diagnostic finding which predicts relapse in patients treated for acute myeloid leukemia. Ultrasensitive detection of minimal residual disease would enable better patient risk stratification and could open opportunities for early therapeutic intervention. Herein we apply single molecule molecular inversion probe capture, a technology combining multiplexed targeted sequencing with error correction schemes based on molecular barcoding, in order to detect mutations identifying minimal residual disease with ultrasensitive and quantitative precision. We designed a single molecule molecular inversion probe capture panel spanning >50 kb and targeting 32 factors relevant to acute myeloid leukemia pathogenesis. We demonstrate linearity and quantitative precision over 100-fold relative abundance of mutant cells (1 in 100 to 1 in 1,500), with estimated error rates approaching 1 in 1,200 base pairs sequenced and maximum theoretical limits of detection exceeding 1 in 60,000 mutant alleles. In 3 of 4 longitudinally collected specimens from patients with acute myeloid leukemia, we find that single molecule molecular inversion probe capture detects somatic mutations identifying minimal residual disease at substantially earlier time points and with greater sensitivity than clinical diagnostic approaches used as current standard of care (flow cytometry and conventional molecular diagnosis), and identifies persisting neoplastic cells during clinical remission. In 2 patients, single molecule molecular inversion probe capture detected heterogeneous, subclonal acute myeloid leukemia populations carrying distinct mutational signatures. Single molecule molecular inversion probe technology uniquely couples scalable target enrichment with sequence read error correction, providing an integrated, ultrasensitive approach for detecting minimal residual disease identifying mutations.

Efficient Identification of Murine M2 Macrophage Peptide Targeting Ligands by Phage Display and Next-Generation Sequencing.

Peptide ligands are used to increase the specificity of drug carriers to their target cells and to facilitate intracellular delivery. One method to identify such peptide ligands, phage display, enables high-throughput screening of peptide libraries for ligands binding to therapeutic targets of interest. However, conventional methods for identifying target binders in a library by Sanger sequencing are low-throughput, labor-intensive, and provide a limited perspective (<0.01%) of the complete sequence space. Moreover, the small sample space can be dominated by nonspecific, preferentially amplifying "parasitic sequences" and plastic-binding sequences, which may lead to the identification of false positives or exclude the identification of target-binding sequences. To overcome these challenges, we employed next-generation Illumina sequencing to couple high-throughput screening and high-throughput sequencing, enabling more comprehensive access to the phage display library sequence space. In this work, we define the hallmarks of binding sequences in next-generation sequencing data, and develop a method that identifies several target-binding phage clones for murine, alternatively activated M2 macrophages with a high (100%) success rate: sequences and binding motifs were reproducibly present across biological replicates; binding motifs were identified across multiple unique sequences; and an unselected, amplified library accurately filtered out parasitic sequences. In addition, we validate the Multiple Em for Motif Elicitation tool as an efficient and principled means of discovering binding sequences.