Chia, Nicholas

Giving birth too soon accounts for half of all newborn deaths worldwide. Clinical symptoms alone are not sufficient to identify women at risk of giving birth too early, as such a pragmatic approach to reducing the incidence of preterm birth entails developing early strategies for intervention before it materializes.

Background Human kidney stones form via repeated events of mineral precipitation, partial dissolution, and reprecipitation, which are directly analogous to similar processes in other natural and manmade environments, where resident microbiomes strongly influence biomineralization. High-resolution microscopy and high-fidelity metagenomic (microscopy-to-omics) analyses, applicable to all forms of biomineralization, have been applied to assemble definitive evidence of in vivo microbiome entombment during urolithiasis. Methods Stone fragments were collected from a randomly chosen cohort of 20 patients using standard percutaneous nephrolithotomy (PCNL). Fourier transform infrared (FTIR) spectroscopy indicated that 18 of these patients were calcium oxalate (CaOx) stone formers, whereas one patient formed each formed brushite and struvite stones. This apportionment is consistent with global stone mineralogy distributions. Stone fragments from seven of these 20 patients (five CaOx, one brushite, and one struvite) were thin sectioned and analyzed using brightfield (BF), polarization (POL), confocal, super-resolution autofluorescence (SRAF), and Raman techniques. DNA from remaining fragments, grouped according to each of the 20 patients, were analyzed with amplicon sequencing of 16S rRNA gene sequences (V1–V3, V3–V5) and internal transcribed spacer (ITS1, ITS2) regions. Results Bulk-entombed DNA was sequenced from stone fragments in 11 of the 18 patients who formed CaOx stones, and the patients who formed brushite and struvite stones. These analyses confirmed the presence of an entombed low-diversity community of bacteria and fungi, including Actinobacteria, Bacteroidetes, Firmicutes , Proteobacteria , and Aspergillus niger . Bacterial cells approximately 1 μm in diameter were also optically observed to be entombed and well preserved in amorphous hydroxyapatite spherules and fans of needle-like crystals of brushite and struvite. Conclusions These results indicate a microbiome is entombed during in vivo CaOx stone formation. Similar processes are implied for brushite and struvite stones. This evidence lays the groundwork for future in vitro and in vivo experimentation to determine how the microbiome may actively and/or passively influence kidney stone biomineralization.

Abstract Incidence rates for endometrial cancer (EC) are rising, particularly in postmenopausal and obese women. Our previous work has showed that the uterine and vaginal microbiome distinguishes patients with EC from those without. We now examine the impact of patient factors (such as menopause status, body mass index, and vaginal pH) in the microbiome in the absence of EC and how these might contribute to the microbiome signature in EC. We find that each factor independently alters the microbiome and identified postmenopausal status as the main driver of a polymicrobial network associated with EC (ECbiome). Of the 17 taxa we found enriched in EC patients, 8 were also enriched by postmenopause. Because postmenopausal status is a main risk factor for endometrial cancer, this system can be thought of as an ecological succession towards a disease state. Organisms within the ECbiome have been previously identified as polymicrobial associations in chronic soft tissue infections, ulcers, morbid obesity, and bacterial vaginosis. This suggests that this microbiome network is likely involved in mechanisms of host disease. Within the ECbiome, Porphyromonas somerae stands out because of its very significant and specific association with EC (p = 5.73E-6; Q = 0.009). We had previously identified this species as significantly associated with EC, and hereby validate that finding. Because the association of P. somerae with EC was robust and specific enough to potentially be considered as a biomarker for the disease (AUC 76.7%, CI: 67.9-85.5%), we developed a P. somerae-specific qPCR assay to detect this species in vaginal swabs. This becomes of particular interest because the lower tract and uterine microbiome are significantly correlated in these patients (p = 0.01), indicating that the vaginal microbiome can be used as a proxy for the uterine environment in EC. In agreement with the 16S rRNA gene sequencing data, P. somerae was detected significantly more frequently in vaginal swabs of patients with EC than those without EC (p = 3.02E-7). Overall, the test achieved a sensitivity of 74% and specificity of 63%, with a positive predictive value of 0.86 for obese and postmenopausal patients. In summary, we identify Porphyromas somerae presence as the most predictive microbial marker of EC, and we confirm this using targeted qPCR, which could be of use in detecting EC in high-risk, asymptomatic women. Given the established pathogenic behavior of P.somerae, we have also explored mechanistic routes through which this microbe and associated consortia may be involved in the mechanisms of disease. Citation Format: Marina Walther-Antonio, Dana Walsh, Alexis Hokenstad, Jun Chen, Jayeun Sung, Gregory Jenkins, Nicholas Chia, Heidi Nelson, Andrea Mariani. Postmenopause as a key factor in the composition of the Endometrial Cancer Microbiome (ECbiome): Putative role of Porphyromonas somerae in the disease [abstract]. In: Proceedings of the AACR Special Conference on the Microbiome, Viruses, and Cancer; 2020 Feb 21-24; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2020;80(8 Suppl):Abstract nr PR09.

Abstract For over 10 years, ModelSEED has been a primary resource for the construction of draft genome-scale metabolic models based on annotated microbial or plant genomes. Now being released, the biochemistry database serves as the foundation of biochemical data underlying ModelSEED and KBase. The biochemistry database embodies several properties that, taken together, distinguish it from other published biochemistry resources by: (i) including compartmentalization, transport reactions, charged molecules and proton balancing on reactions; (ii) being extensible by the user community, with all data stored in GitHub; and (iii) design as a biochemical ‘Rosetta Stone’ to facilitate comparison and integration of annotations from many different tools and databases. The database was constructed by combining chemical data from many resources, applying standard transformations, identifying redundancies and computing thermodynamic properties. The ModelSEED biochemistry is continually tested using flux balance analysis to ensure the biochemical network is modeling-ready and capable of simulating diverse phenotypes. Ontologies can be designed to aid in comparing and reconciling metabolic reconstructions that differ in how they represent various metabolic pathways. ModelSEED now includes 33,978 compounds and 36,645 reactions, available as a set of extensible files on GitHub, and available to search at https://modelseed.org/biochem and KBase.

Abstract Motivation While each cancer is the result of an isolated evolutionary process, there are repeated patterns in tumorigenesis defined by recurrent driver mutations and their temporal ordering. Such repeated evolutionary trajectories hold the potential to improve stratification of cancer patients into subtypes with distinct survival and therapy response profiles. However, current cancer phylogeny methods infer large solution spaces of plausible evolutionary histories from the same sequencing data, obfuscating repeated evolutionary patterns. Results To simultaneously resolve ambiguities in sequencing data and identify cancer subtypes, we propose to leverage common patterns of evolution found in patient cohorts. We first formulate the Multiple Choice Consensus Tree problem, which seeks to select a tumor tree for each patient and assign patients into clusters in such a way that maximizes consistency within each cluster of patient trees. We prove that this problem is NP-hard and develop a heuristic algorithm, Revealing Evolutionary Consensus Across Patients (RECAP), to solve this problem in practice. Finally, on simulated data, we show RECAP outperforms existing methods that do not account for patient subtypes. We then use RECAP to resolve ambiguities in patient trees and find repeated evolutionary trajectories in lung and breast cancer cohorts. Availability and implementation https://github.com/elkebir-group/RECAP. Supplementary information Supplementary data are available at Bioinformatics online.

The vaginal microbiome is a critical component of women’s sexual and reproductive health, with variations in microbial composition, particularly the loss of Lactobacillus species, being implicated in gynecologic and obstetric diseases. Given that the vaginal microbiome is so crucial, why do vaginal microbial profiles vary strikingly from person to person and even change over time within the same person? In the present study, which tracked the daily vaginal microbiomes of young healthy women through different lifestyles, we found that use of a locally released progestin contraceptive, a vegetarian diet, and intense exercise appear to lead to vaginal microbiome alterations and loss of Lactobacillus species. The impact of these vaginal microbiome changes on immediate and long-term health remain to be investigated.

A major direction for future microbiome research is implementation of fecal sample collections in large-scale, prospective epidemiologic studies. Studying microbiome-disease associations likely requires microbial data to be pooled from multiple studies. Our findings suggest collection methods that are most optimal to be used standardly across future WGSS microbiome studies.

Colorectal adenomas are precursors of CRC. Recently, the gut microbiota, i.e., the collection of microbes residing in our gut, has been recognized as a key player in CRC development. There have been a number of gut microbiota profiling studies for colorectal adenoma and CRC; however, fewer studies have considered the gut metabolome, which serves as the chemical interface between the host and gut microbiota. Here, we conducted a gut metabolome profiling study of colorectal adenoma and CRC and analyzed the metabolomic profiles together with paired microbiota composition profiles. We found several chemical signatures of colorectal adenoma that were associated with some gut microbes and potentially indicative of future CRC. This study highlights potential early-driver metabolites in CRC pathogenesis and guides further targeted experiments and thus provides an important stepping stone toward developing better CRC prevention strategies.