Pseudomonas aeruginosa ventricular assist device infections: findings from ineffective phage therapies in five cases

Left ventricular assist devices (LVAD) are increasingly used for management of heart failure; infection remains a frequent complication. Phage therapy has been successful in a variety of antibiotic refractory infections and is of interest in treating LVAD infections. We performed a retrospective review of four patients that underwent five separate courses of intravenous (IV) phage therapy with concomitant antibiotic for treatment of endovascular Pseudomonas aeruginosa LVAD infection. We assessed phage susceptibility, bacterial strain sequencing, serum neutralization, biofilm activity, and shelf-life of phage preparations. Five treatments of one to four wild-type virulent phage(s) were administered for 14-51 days after informed consent and regulatory approval. There was no successful outcome. Breakthrough bacteremia occurred in four of five treatments. Two patients died from the underlying infection. We noted a variable decline in phage susceptibility following three of five treatments, four of four tested developed serum neutralization, and prophage presence was confirmed in isolates of two tested patients. Two phage preparations showed an initial titer drop. Phage biofilm activity was confirmed in two. Phage susceptibility alone was not predictive of clinical efficacy in P. aeruginosa endovascular LVAD infection. IV phage was associated with serum neutralization in most cases though lack of clinical effect may be multifactorial including presence of multiple bacterial isolates with varying phage susceptibility, presence of prophages, decline in phage titers, and possible lack of biofilm activity. Breakthrough bacteremia occurred frequently (while the organism remained susceptible to administered phage) and is an important safety consideration.

Genetic hypogonadal mouse model reveals niche-specific influence of reproductive axis and sex on intestinal microbial communities

BACKGROUND

The gut microbiome has been linked to many diseases with sex bias including autoimmune, metabolic, neurological, and reproductive disorders. While numerous studies report sex differences in fecal microbial communities, the role of the reproductive axis in this differentiation is unclear and it is unknown how sex differentiation affects microbial diversity in specific regions of the small and large intestine.

METHODS

We used a genetic hypogonadal mouse model that does not produce sex steroids or go through puberty to investigate how sex and the reproductive axis impact bacterial diversity within the intestine. Using 16S rRNA gene sequencing, we analyzed alpha and beta diversity and taxonomic composition of fecal and intestinal communities from the lumen and mucosa of the duodenum, ileum, and cecum from adult female (n = 20) and male (n = 20) wild-type mice and female (n = 17) and male (n = 20) hypogonadal mice.

RESULTS

Both sex and reproductive axis inactivation altered bacterial composition in an intestinal section and niche-specific manner. Hypogonadism was significantly associated with bacteria from the Bacteroidaceae, Eggerthellaceae, Muribaculaceae, and Rikenellaceae families, which have genes for bile acid metabolism and mucin degradation. Microbial balances between males and females and between hypogonadal and wild-type mice were also intestinal section-specific. In addition, we identified 3 bacterial genera (Escherichia Shigella, Lachnoclostridium, and Eggerthellaceae genus) with higher abundance in wild-type female mice throughout the intestinal tract compared to both wild-type male and hypogonadal female mice, indicating that activation of the reproductive axis leads to female-specific differentiation of the gut microbiome. Our results also implicated factors independent of the reproductive axis (i.e., sex chromosomes) in shaping sex differences in intestinal communities. Additionally, our detailed profile of intestinal communities showed that fecal samples do not reflect bacterial diversity in the small intestine.

CONCLUSIONS

Our results indicate that sex differences in the gut microbiome are intestinal niche-specific and that sampling feces or the large intestine may miss significant sex effects in the small intestine. These results strongly support the need to consider both sex and reproductive status when studying the gut microbiome and while developing microbial-based therapies.

Sex, puberty, and the gut microbiome

In brief

Sex differences in the gut microbiome may impact multiple aspects of human health and disease. In this study, we review the evidence for microbial sex differences in puberty and adulthood and discuss potential mechanisms driving differentiation of the sex-specific gut microbiome.

Abstract

In humans, the gut microbiome is strongly implicated in numerous sex-specific physiological processes and diseases. Given this, it is important to understand how sex differentiation of the gut microbiome occurs and how these differences contribute to host health and disease. While it is commonly believed that the gut microbiome stabilizes after 3 years of age, our review of the literature found considerable evidence that the gut microbiome continues to mature during and after puberty in a sex-dependent manner. We also review the intriguing, though sparse, literature on potential mechanisms by which host sex may influence the gut microbiome, and vice versa, via sex steroids, bile acids, and the immune system. We conclude that the evidence for the existence of a sex-specific gut microbiome is strong but that there is a dearth of research on how host-microbe interactions lead to this differentiation. Finally, we discuss the types of future studies needed to understand the processes driving the maturation of sex-specific microbial communities and the interplay between gut microbiota, host sex, and human health.

Co-targeting KRAS G12C and EGFR reduces both mutant and wild-type RAS-GTP

The combination of KRAS G12C inhibitors with EGFR inhibitors has reproducibly been shown to be beneficial. Here, we identify another benefit of this combination: it effectively inhibits both wild-type and mutant RAS. We believe that targeting both mutant and wild-type RAS helps explain why this combination of inhibitors is effective.

Altered microbiomes in thirdhand smoke-exposed children and their home environments

INTRODUCTION

Tobacco smoke contains numerous toxic chemicals that accumulate in indoor environments creating thirdhand smoke (THS). We investigated if THS-polluted homes differed in children's human and built-environment microbiomes as compared to THS-free homes.

METHODS

Participants were n = 19 THS-exposed children and n = 10 unexposed children (≤5 years) and their caregivers. Environmental and biological samples were analyzed for THS pollutants and exposure. Swab samples were collected from the built-environment (floor, table, armrest, bed frame) and child (finger, nose, mouth, and ear canal), and 16S ribosomal RNA genes were analyzed for bacterial taxa using high-throughput DNA sequencing.

RESULTS

Phylogenetic α-diversity was significantly higher for the built-environment microbiomes in THS-polluted homes compared to THS-free homes (p < 0.014). Log2-fold comparison found differences between THS-polluted and THS-free homes for specific genera in samples from the built-environment (e.g., Acinetobacter, Bradyrhizobium, Corynebacterium, Gemella, Neisseria, Staphylococcus, Streptococcus, and Veillonella) and in samples from children (esp. Corynebacterium, Gemella, Lautropia, Neisseria, Rothia, Staphylococcus, and Veillonella).

CONCLUSION

When exposed to THS, indoor and children microbiomes are altered in an environment-specific manner. Changes are similar to those reported in previous studies for smokers and secondhand smoke-exposed persons. THS-induced changes in child and built-environmental microbiomes may play a role in clinical outcomes in children.

IMPACT

Despite smoking bans, children can be exposed to tobacco smoke residue (i.e., thirdhand smoke) that lingers on surfaces and in settled house dust. Thirdhand smoke exposure is associated with changes in the microbiomes of the home environment and of the children living in these homes. Thirdhand smoke is associated with increased phylogenetic diversity of the home environment and changes in the abundances of several genera of the child microbiome known to be affected by active smoking and secondhand smoke (e.g., Corynebacterium, Staphylococcus, Streptococcus). Thirdhand smoke exposure by itself may induce alterations in the microbiome that play a role in childhood pathologies.

Compositional Data Analysis of Periodontal Disease Microbial Communities

Periodontal disease (PD) is a chronic, progressive polymicrobial disease that induces a strong host immune response. Culture-independent methods, such as next-generation sequencing (NGS) of bacteria 16S amplicon and shotgun metagenomic libraries, have greatly expanded our understanding of PD biodiversity, identified novel PD microbial associations, and shown that PD biodiversity increases with pocket depth. NGS studies have also found PD communities to be highly host-specific in terms of both biodiversity and the response of microbial communities to periodontal treatment. As with most microbiome work, the majority of PD microbiome studies use standard data normalization procedures that do not account for the compositional nature of NGS microbiome data. Here, we apply recently developed compositional data analysis (CoDA) approaches and software tools to reanalyze multiomics (16S, metagenomics, and metabolomics) data generated from previously published periodontal disease studies. CoDA methods, such as centered log-ratio (clr) transformation, compensate for the compositional nature of these data, which can not only remove spurious correlations but also allows for the identification of novel associations between microbial features and disease conditions. We validated many of the studies’ original findings, but also identified new features associated with periodontal disease, including the genera Schwartzia and Aerococcus and the cytokine C-reactive protein (CRP). Furthermore, our network analysis revealed a lower connectivity among taxa in deeper periodontal pockets, potentially indicative of a more “random” microbiome. Our findings illustrate the utility of CoDA techniques in multiomics compositional data analysis of the oral microbiome.

An application of compositional data analysis to multiomic time-series data

Compositional data analysis (CoDA) methods have increased in popularity as a new framework for analyzing next-generation sequencing (NGS) data. CoDA methods, such as the centered log-ratio (clr) transformation, adjust for the compositional nature of NGS counts, which is not addressed by traditional normalization methods. CoDA has only been sparsely applied to NGS data generated from microbial communities or to multiple ‘omics’ datasets. In this study, we applied CoDA methods to analyze NGS and untargeted metabolomic datasets obtained from bacterial and fungal communities. Specifically, we used clr transformation to reanalyze NGS amplicon and metabolomics data from a study investigating the effects of building material type, moisture and time on microbial and metabolomic diversity. Compared to analysis of untransformed data, analysis of clr-transformed data revealed novel relationships and stronger associations between sample conditions and microbial and metabolic community profiles.

Abstract B43: A systems biology approach to elucidate the mechanism of EGFR inhibitor sensitivity in mutant KRAS-driven colorectal cancer

Standard protocol to treat colorectal cancer (CRC) includes surgery, chemotherapy and radiotherapy as first-line treatment options. When applicable, targeting agents such as anti-EGFR therapies (i.e., cetuximab and panitumumab) have become important long-term neoadjuvant therapies that increase survival in some patients. In recent years it has become common practice to sequence patients and their tumor specimens’ DNA. This recent push in genomic medicine has led to the identification that 30-40% of CRC patient harbor an activating KRAS mutation. These mutations are thought to be an early driver in the cancer’s progression. KRAS is also considered to be the key player in conferring resistance to the anti-EGFR treatments cetuximab and panitumumab. That Ras mutations confer resistance to EGFR inhibitors is intuitive. In recent years, clinical guidelines have extended the list of contraindicated genotypes to many mutations in both the KRAS and NRAS genes. In contrast with the current guidelines for managing CRC with EGFR inhibitors, it has been shown that patients harboring a KRAS G13D mutation are sensitive to cetuximab. This has been reproducibly shown in both in vitro and in vivo model systems and is supported by retrospective analysis of initial clinical trial data. The current mutant-RAS restrictive guidelines are supported by a method that relied upon the grouping of all common Ras mutations as “equal,” which potentially washes out less common yet sensitive mutations. Whether KRAS G13D mutations are sensitive to cetuximab has remained a controversial topic for many years due to the lack of understanding of a mechanism, as it is counterintuitive to the current understanding of EGFR signaling cascade. We here identify a novel mechanism by which G13D RAS mutant is sensitive to EGFR inhibition by a nonintuitive process of reliance upon WT RAS molecules. We utilized a computational model of RAS signaling previously developed by our laboratory to explore mutant Ras signaling and thereby investigated the controversial response of KRAS G13D to anti-EGFR agents. Our computational studies of the historically reported biochemical processes that regulate Ras signals reveal a nonintuitive, mutant-specific dependency of wild-type RAS activation on EGFR. The model also reveals this dependency is determined by the interaction strength between a KRAS mutant and tumor suppressor neurofibromin. Our prospective experiments confirm this mechanism that arises from the systems-level regulation of Ras pathway signaling. Overall, our work demonstrates how systems approaches enable mechanism-based inference in genomic medicine.

Citation Format: Thomas McFall, Jolene Diedrich, Stacy L. Littlechild, Laura Sisk-Hackworth, James Moresco, Meron Mengistu1, Andrey Shaw, Ed Stites. A systems biology approach to elucidate the mechanism of EGFR inhibitor sensitivity in mutant KRAS-driven colorectal cancer [abstract]. In: Proceedings of the AACR Special Conference on Targeting RAS-Driven Cancers; 2018 Dec 9-12; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Res 2020;18(5_Suppl):Abstract nr B43.

Meta-SourceTracker: application of Bayesian source tracking to shotgun metagenomics

Background

Microbial source tracking methods are used to determine the origin of contaminating bacteria and other microorganisms, particularly in contaminated water systems. The Bayesian SourceTracker approach uses deep-sequencing marker gene libraries (16S ribosomal RNA) to determine the proportional contributions of bacteria from many potential source environments to a given sink environment simultaneously. Since its development, SourceTracker has been applied to an extensive diversity of studies, from beach contamination to human behavior.

Methods

Here, we demonstrate a novel application of SourceTracker to work with metagenomic datasets and tested this approach using sink samples from a study of coastal marine environments. Source environment metagenomes were obtained from metagenomics studies of gut, freshwater, marine, sand and soil environments. As part of this effort, we implemented features for determining the stability of source proportion estimates, including precision visualizations for performance optimization, and performed domain-specific source-tracking analyses (i.e., Bacteria, Archaea, Eukaryota and viruses). We also applied SourceTracker to metagenomic libraries generated from samples collected from the International Space Station (ISS).

Results

SourceTracker proved highly effective at predicting the composition of known sources using shotgun metagenomic libraries. In addition, we showed that different taxonomic domains sometimes presented highly divergent pictures of environmental source origins for both the coastal marine and ISS samples. These findings indicated that applying SourceTracker to separate domains may provide a deeper understanding of the microbial origins of complex, mixed-source environments, and further suggested that certain domains may be preferable for tracking specific sources of contamination.

A systems mechanism for KRAS mutant allele-specific responses to targeted therapy

Cancer treatment decisions are increasingly guided by which specific genes are mutated within each patient's tumor. For example, agents inhibiting the epidermal growth factor receptor (EGFR) benefit many colorectal cancer (CRC) patients, with the general exception of those whose tumor includes a KRAS mutation. However, among the various KRAS mutations, that which encodes the G13D mutant protein (KRAS^G13D) behaves differently; for unknown reasons, KRAS^G13D CRC patients benefit from the EGFR-blocking antibody cetuximab. Controversy surrounds this observation, because it contradicts the well-established mechanisms of EGFR signaling with regard to RAS mutations. Here, we identified a systems-level, mechanistic explanation for why KRAS^G13D cancers respond to EGFR inhibition. A computational model of RAS signaling revealed that the biophysical differences between the three most common KRAS mutants were sufficient to generate different sensitivities to EGFR inhibition. Integrated computation with experimentation then revealed a nonintuitive, mutant-specific dependency of wild-type RAS activation by EGFR that is determined by the interaction strength between KRAS and the tumor suppressor neurofibromin (NF1). KRAS mutants that strongly interacted with and competitively inhibited NF1 drove wild-type RAS activation in an EGFR-independent manner, whereas KRAS^G13D weakly interacted with and could not competitively inhibit NF1 and, thus, KRAS^G13D cells remained dependent on EGFR for wild-type RAS activity. Overall, our work demonstrates how systems approaches enable mechanism-based inference in genomic medicine and can help identify patients for selective therapeutic strategies.