Dynamical model of antibiotic responses linking expression of resistance genes to metabolism explains emergence of heterogeneity during drug exposures.

Antibiotic responses in bacteria are highly dynamic and heterogeneous, with sudden exposure of bacterial colonies to high drug doses resulting in the coexistence of recovered and arrested cells. The dynamics of the response is determined by regulatory circuits controlling the expression of resistance genes, which are in turn modulated by the drug's action on cell growth and metabolism. Despite advances in understanding gene regulation at the molecular level, we still lack a framework to describe how feedback mechanisms resulting from the interdependence between expression of resistance and cell metabolism can amplify naturally occurring noise and create heterogeneity at the population level. To understand how this interplay affects cell survival upon exposure, we constructed a mathematical model of the dynamics of antibiotic responses that links metabolism and regulation of gene expression, based on the tetracycline resistancetetoperon inE. coli. We use this model to interpret measurements of growth and expression of resistance in microfluidic experiments, both in single cells and in biofilms. We also implemented a stochastic model of the drug response, to show that exposure to high drug levels results in large variations of recovery times and heterogeneity at the population level. We show that stochasticity is important to determine how nutrient quality affects cell survival during exposure to high drug concentrations. A quantitative description of how microbes respond to antibiotics in dynamical environments is crucial to understand population-level behaviors such as biofilms and pathogenesis.

A novel method to assess copy number variations in melanocytic neoplasms: Droplet digital PCR for precise quantitation of MYC and MYB genes.

INTRODUCTION: While most melanocytic neoplasms can be classified as either benign or malignant by histopathology alone, ancillary molecular diagnostic tests can be necessary to establish the correct diagnosis in challenging cases. Currently, the detection of copy number variations (CNVs) by fluorescence in situ hybridization and chromosomal microarray (CMA) are the most popular methods, but remain expensive and inaccessible. We aim to develop a relatively inexpensive, fast, and accessible molecular assay to detect CNVs relevant to melanoma using droplet digital polymerase chain reaction (ddPCR) technology. METHODS: In this proof-of-concept study, we evaluated CNVs in MYC and MYB genes from 73 cases of benign nevi, borderline melanocytic lesions, and primary and metastatic melanoma at our institution from 2015 to 2022. A multiplexed ddPCR assay and CMA were performed on each sample, and the results were compared. RESULTS: Concordance analysis of ddPCR with CMA for quantification of MYC and MYB CNVs revealed a sensitivity and specificity of 89% and 86% for MYC and 83% and 74% for MYB, respectively. CONCLUSION: We demonstrate the first use of a multiplexed ddPCR assay to identify CNVs in melanocytic neoplasms. With further improvement and validation, ddPCR may represent a low-cost and rapid tool to aid in the diagnosis of histopathologically ambiguous melanocytic tumors.

Anti-PL-7, anti-Ro/SSA, anti-Mi-2, and anti-TIF1-γ correlate with specific patterns of histopathologic features in dermatomyositis: An analysis of 39 skin biopsy specimens from 25 patients.

BACKGROUND: In dermatomyositis (DM), myositis-specific and myositis-associated antibodies have been correlated with clinical features. It is unknown if histopathologic findings in lesional skin biopsies correlate with serologic subtypes of DM. METHODS: A retrospective chart review of patients with DM was performed. Patients with myositis antibodies and DM lesional skin biopsies were included in the study. Skin biopsies were reviewed by blinded dermatopathologists for 20 histopathologic features. RESULTS: There was a statistically significant (p < 0.05) association between anti-PL-7 serology and decreased degree of vacuolar degeneration, necrotic keratinocytes, and thickening of the epidermal basement membrane. Anti-aminoacyl tRNA synthetase (anti-ARS) antibodies had the same significant negative association with degree of vacuolar degeneration, necrotic keratinocytes, and thickening of the epidermal basement membrane. A similar pattern was seen with an anti-cytoplasmic serology; where there was a significant association with an increased degree of vacuolar degeneration and necrotic keratinocytes, and a nonsignificant trend of minimally thickened epidermal basement membrane. There was a statistically significant association between anti-Ro/SSA serology and increased degree of vacuolar degeneration. Anti-TIF1-γ serology was significantly associated with the increased presence of necrotic keratinocytes and pigment incontinence, and displayed a pattern of increased neutrophils. There was a significant association between anti-Mi-2 antibodies and pigment incontinence, as well as between myositis-specific antibodies and pigment incontinence. A statistically significant positive association was found between nuclear antibodies and degree of vacuolar degeneration, thickened epidermal basement membrane, pigment incontinence, and epidermal atrophy. CONCLUSION: In patients with DM, some specific serotypes, including anti-PL-7, anti-Ro/SSA, anti-Mi-2, and anti-TIF1-γ, may have characteristic histopathologic features.

Dynamical model of antibiotic responses linking expression of resistance to metabolism explains emergence of heterogeneity during drug exposures.

Antibiotic responses in bacteria are highly dynamic and heterogeneous, with sudden exposure of bacterial colonies to high drug doses resulting in the coexistence of recovered and arrested cells. The dynamics of the response is determined by regulatory circuits controlling the expression of resistance genes, which are in turn modulated by the drug's action on cell growth and metabolism. Despite advances in understanding gene regulation at the molecular level, we still lack a framework to describe how feedback mechanisms resulting from the interdependence between expression of resistance and cell metabolism can amplify naturally occurring noise and create heterogeneity at the population level. To understand how this interplay affects cell survival upon exposure, we constructed a mathematical model of the dynamics of antibiotic responses that links metabolism and regulation of gene expression, based on the tetracycline resistance tet operon in E. coli. We use this model to interpret measurements of growth and expression of resistance in microfluidic experiments, both in single cells and in biofilms. We also implemented a stochastic model of the drug response, to show that exposure to high drug levels results in large variations of recovery times and heterogeneity at the population level. We show that stochasticity is important to determine how nutrient quality affects cell survival during exposure to high drug concentrations. A quantitative description of how microbes respond to antibiotics in dynamical environments is crucial to understand population-level behaviors such as biofilms and pathogenesis.

Nationwide survey of medical student interest in and exposure to aerospace medicine.

Aerospace Medicine is experiencing a renaissance. Commercial spaceflight is now a reality, meaning that individuals with a variety of medical conditions will be flying in space. NASA has Mars plans, and SpaceX plans to send humans to Mars within the next decade, so today's medical students may be future physicians on these crews. Considering these developments, we evaluated interest in and exposure to Aerospace Medicine among medical students in the United States (US). A 19-question anonymous multiple-choice questionnaire was emailed to current medical students throughout the US. Information about demographics, career and research interests in aerospace medicine, opportunities available at students' respective institutions, and possible avenues for supporting students' interests was collected and analyzed. One thousand two hundred forty-four students (490 men, 751 women, 3 other) with a mean age of 25.8 ± 3.0 years from 60 institutions completed the questionnaire. Most respondents expressed an interest in learning about aerospace medicine during their training. A strong interest in research, as well as career opportunities, exists despite the majority of students reporting minimal access to opportunities to get involved in the field at most of the surveyed institutions. With growing interest and an expected increase in demand for physicians with a background in aerospace medicine, medical schools may be able to support students by increasing access to opportunities.

Pre-flight body weight effects on urinary calcium excretion in space.

Microgravity-induced bone loss increases urinary calcium excretion which increases kidney stone formation risk. Not all individuals show the same degree of increase in urinary calcium and some pre-flight characteristics may help identify individuals who may benefit from in-flight monitoring. In weightlessness the bone is unloaded, and the effect of this unloading may be greater for those who weigh more. We studied whether pre-flight body weight was associated with increased in-flight urinary calcium excretion using data from Skylab and the International Space Station (ISS). The study was reviewed and approved by the National Aeronautics and Space Administration (NASA) electronic Institutional Review Board (eIRB) and data were sourced from the Longitudinal Study of Astronaut Health (LSAH) database. The combined Skylab and ISS data included 45 participants (9 Skylab, 36 ISS). Both weight and day in flight were positively related to urinary calcium excretion. There was also an interaction between weight and day in flight with higher weight associated with higher calcium excretion earlier in the mission. This study shows that pre-flight weight is also a factor and could be included in the risk assessments for bone loss and kidney stone formation in space.

A Novel Method to Detect Copy Number Variation in Melanoma: Droplet Digital PCR for Quantitation of the CDKN2A Gene, a Proof-of-Concept Study.

ABSTRACT: A definitive diagnosis of nevus or melanoma is not always possible for histologically ambiguous melanocytic neoplasms. In such cases, ancillary molecular testing can support a diagnosis of melanoma if certain chromosomal aberrations are detected. Current technologies for copy number variation (CNV) detection include chromosomal microarray analysis (CMA) and fluorescence in situ hybridization. Although CMA and fluorescence in situ hybridization are effective, their utilization can be limited by cost, turnaround time, and inaccessibility outside of large reference laboratories. Droplet digital polymerase chain reaction (ddPCR) is a rapid, automated, and relatively inexpensive technology for CNV detection. We investigated the ability of ddPCR to quantify CNV in cyclin-dependent kinase inhibitor 2A ( CDKN2A ), the most commonly deleted tumor suppressor gene in melanoma. CMA data were used as the gold standard. We analyzed 57 skin samples from 52 patients diagnosed with benign nevi, borderline lesions, primary melanomas, and metastatic melanomas. In a training cohort comprising 29 randomly selected samples, receiver operator characteristic curve analysis revealed an optimal ddPCR cutoff value of 1.73 for calling CDKN2A loss. In a validation cohort comprising the remaining 28 samples, ddPCR detected CDKN2A loss with a sensitivity and specificity of 94% and 90%, respectively. Significantly, ddPCR could also identify whether CDKN2A losses were monoallelic or biallelic. These pilot data suggest that ddPCR can detect CDKN2A deletions in melanocytic tumors with accuracy comparable with CMA. With further validation, ddPCR could provide an additional CNV assay to aid in the diagnosis of challenging melanocytic neoplasms.

Gain of CCND1 May Occur Too Infrequently in Cutaneous Melanoma, and Too Late in Melanomagenesis, to Be Diagnostically Useful: Genomic Analysis of 88 Cases.

ABSTRACT: Genomic analysis is an important tool in the diagnosis of histologically ambiguous melanocytic neoplasms. Melanomas, in contrast to nevi, are characterized by the presence of multiple copy number alterations. One such alteration is gain of the proto-oncogene CCND1 at 11q13. In melanoma, gain of CCND1 has been reported in approximately one-fifth of cases. Exact frequencies of CCND1 gain vary by melanoma subtype, ranging from 15.8% for lentigo maligna to 25.1% for acral melanoma. We present a cohort of 72 cutaneous melanomas from 2017-2022 in which only 6 (8.3%) showed evidence of CCND1 gain by chromosomal microarray. This CCND1 upregulation frequency falls well below those previously published and is significantly lower than estimated in the literature ( P < 0.05). In addition, all 6 melanomas with CCND1 gain had copy number alterations at other loci (most commonly CDKN2A loss, followed by RREB1 gain), and 5 were either thick or metastatic lesions. This suggests that CCND1 gene amplification may be a later event in melanomagenesis, long after a lesion would be borderline or equivocal by histology. Data from fluorescence in situ hybridization, performed on 16 additional cutaneous melanomas, further corroborate our findings. CCND1 gain may not be a common alteration in melanoma and likely occurs too late in melanomagenesis to be diagnostically useful. We present the largest chromosomal microarray analysis of CCND1 upregulation frequencies in cutaneous melanoma, conjecture 3 hypotheses to explain our novel observation, and discuss implications for the inclusion or exclusion of CCND1 probes in future melanoma gene panels.

A novel method to assess copy number variation in melanoma: Droplet digital PCR for precise quantitation of the RREB1 gene in formalin-fixed, paraffin-embedded melanocytic neoplasms, a proof-of-concept study.

BACKGROUND: Melanocytic neoplasms can be challenging to diagnose. One well-established diagnostic aid is the detection of copy number variation (CNV) in a few key genetic loci using conventional methods such as fluorescence in situ hybridization (FISH) and chromosomal microarray (CMA). Droplet digital polymerase chain reaction (ddPCR) is a novel, cost-effective, rapid, and automated method to detect CNV. METHODS: We perform the first investigation of ddPCR to assay Ras-responsive element-binding protein-1 (RREB1), the most common CNV in melanoma using formalin-fixed, paraffin-embedded (FFPE) melanocytic lesion samples; CMA data are used as the gold standard. Archival samples from 2013 to 2021 were analyzed, including 153 data points from 39 FFPE samples representing 34 patients. Benign, borderline, malignant, and metastatic melanocytic neoplasms were examined. RESULTS: ddPCR showed a sensitivity and specificity of 93.8% and 95.7% using one reference gene, and 87.5% and 100% using a different reference gene for RREB1 gain detection. CONCLUSIONS: Here we show that ddPCR can provide inexpensive, rapid, and robust data on the commonest copy number alteration in melanoma. Future development and validation could provide a useful ancillary tool in the diagnosis of challenging melanocytic lesions.

Optimal transcriptional regulation of dynamic bacterial responses to sudden drug exposures.

Cellular responses to the presence of toxic compounds in their environment require prompt expression of the correct levels of the appropriate enzymes, which are typically regulated by transcription factors that control gene expression for the duration of the response. The characteristics of each response dictate the choice of regulatory parameters such as the affinity of the transcription factor to its binding sites and the strength of the promoters it regulates. Although much is known about the dynamics of cellular responses, we still lack a framework to understand how different regulatory strategies evolved in natural systems relate to the selective pressures acting in each particular case. Here, we analyze a dynamical model of a typical antibiotic response in bacteria, where a transcriptionally repressed enzyme is induced by a sudden exposure to the drug that it processes. We identify strategies of gene regulation that optimize this response for different types of selective pressures, which we define as a set of costs associated with the drug, enzyme, and repressor concentrations during the response. We find that regulation happens in a limited region of the regulatory parameter space. While responses to more costly (toxic) drugs favor the usage of strongly self-regulated repressors, responses where expression of enzyme is more costly favor the usage of constitutively expressed repressors. Only a very narrow range of selective pressures favor weakly self-regulated repressors. We use this framework to determine which costs and benefits are most critical for the evolution of a variety of natural cellular responses that satisfy the approximations in our model and to analyze how regulation is optimized in new environments with different demands.

Nutrient Gradients Mediate Complex Colony-Level Antibiotic Responses in Structured Microbial Populations.

Antibiotic treatments often fail to eliminate bacterial populations due to heterogeneity in how individual cells respond to the drug. In structured bacterial populations such as biofilms, bacterial metabolism and environmental transport processes lead to an emergent phenotypic structure and self-generated nutrient gradients toward the interior of the colony, which can affect cell growth, gene expression and susceptibility to the drug. Even in single cells, survival depends on a dynamic interplay between the drug's action and the expression of resistance genes. How expression of resistance is coordinated across populations in the presence of such spatiotemporal environmental coupling remains elusive. Using a custom microfluidic device, we observe the response of spatially extended microcolonies of tetracycline-resistant E. coli to precisely defined dynamic drug regimens. We find an intricate interplay between drug-induced changes in cell growth and growth-dependent expression of resistance genes, resulting in the redistribution of metabolites and the reorganization of growth patterns. This dynamic environmental feedback affects the regulation of drug resistance differently across the colony, generating dynamic phenotypic structures that maintain colony growth during exposure to high drug concentrations and increase population-level resistance to subsequent exposures. A mathematical model linking metabolism and the regulation of gene expression is able to capture the main features of spatiotemporal colony dynamics. Uncovering the fundamental principles that govern collective mechanisms of antibiotic resistance in spatially extended populations will allow the design of optimal drug regimens to counteract them.

Metabolic basis for the evolution of a common pathogenic Pseudomonas aeruginosa variant.

Microbes frequently evolve in reproducible ways. Here, we show that differences in specific metabolic regulation rather than inter-strain interactions explain the frequent presence of lasR loss-of-function (LOF) mutations in the bacterial pathogen Pseudomonas aeruginosa. While LasR contributes to virulence through its role in quorum sensing, lasR mutants have been associated with more severe disease. A model based on the intrinsic growth kinetics for a wild type strain and its LasR- derivative, in combination with an experimental evolution based genetic screen and further genetics analyses, indicated that differences in metabolism were sufficient to explain the rise of these common mutant types. The evolution of LasR- lineages in laboratory and clinical isolates depended on activity of the two-component system CbrAB, which modulates substrate prioritization through the catabolite repression control pathway. LasR- lineages frequently arise in cystic fibrosis lung infections and their detection correlates with disease severity. Our analysis of bronchoalveolar lavage fluid metabolomes identified compounds that negatively correlate with lung function, and we show that these compounds support enhanced growth of LasR- cells in a CbrB-controlled manner. We propose that in vivo metabolomes contribute to pathogen evolution, which may influence the progression of disease and its treatment.

Bacteria can evolve quickly, a skill that proves useful in ever-changing environments. For example, individuals in many bacterial species can start to work together under certain circumstances; this ability is underpinned by a system called quorum sensing, which allows cells to detect nearby conspecifics. However, species of harmful bacteria often lose their quorum sensing abilities when they infect humans. This is the case for Pseudomonas aeruginosa, which normally lives in the soil but can also cause deadly conditions, especially in hospital settings. Patients often carry P. aeruginosa with mutations that disable the quorum-sensing signal receptor LasR, a molecular actor that can switch on many other genes in a cell. People who are infected with P. aeruginosa strains carrying a damaged version of the lasR gene are typically more ill and less likely to recover. Why this is the case ­ and in fact, why genes associated with quorum sensing often lose function during infection ­ is still unclear. To investigate this question, Mould et al. used laboratory evolution experiments and computer models of P. aeruginosa growth to understand how lasR mutant cells evolve. Differences in growth rates and ways to use resources (rather than changes in cell-to-cell interactions) best explained why lasR mutants become more successful. Further experiments narrowed down the molecular cascade required for the rise of lasR mutants, identifying a pathway that regulates how P. aeruginosa switches between different nutrient sources. This work reveals a new connection between quorum sensing genes and nutrient regulation in bacterial cells. Loss of functional LasR changes the way that cells use nutrients, and thus will reshape how they interact with host cells and other bacteria. This insight could lead to better ways to predict the outcomes of bacterial infections and how to best treat them.