Nitrogen, sulfur and carbon fluxes in the terrestrial subsurface are determined by the intersecting activities of microbial community members, yet the organisms responsible are largely unknown. Metagenomic methods can identify organisms and functions, but genome recovery is often precluded by data complexity. To address this limitation, we developed subsampling assembly methods to re-construct high-quality draft genomes from complex samples. We applied these methods to evaluate the interlinked roles of the most abundant organisms in biogeochemical cycling in the aquifer sediment. Community proteomics confirmed these activities. The eight most abundant organisms belong to novel lineages, and two represent phyla with no previously sequenced genome. Four organisms are predicted to fix carbon via the Calvin-Benson-Bassham, Wood-Ljungdahl or 3-hydroxyproprionate/4-hydroxybutarate pathways. The profiled organisms are involved in the network of denitrification, dissimilatory nitrate reduction to ammonia, ammonia oxidation and sulfate reduction/oxidation, and require substrates supplied by other community members. An ammonium-oxidizing Thaumarchaeote is the most abundant community member, despite low ammonium concentrations in the groundwater. This organism likely benefits from two other relatively abundant organisms capable of producing ammonium from nitrate, which is abundant in the groundwater. Overall, dominant members of the microbial community are interconnected through exchange of geochemical resources.

Objective

Amyotrophic lateral sclerosis (ALS) is a heterogeneous disease with a complex etiology that lacks biomarkers predicting disease progression. The objective of this study was to use longitudinal cerebrospinal fluid (CSF) samples to identify biomarkers that distinguish fast progression (FP) from slow progression (SP) and assess their temporal response.

Methods

We utilized mass spectrometry (MS)-based proteomics to identify candidate biomarkers using longitudinal CSF from a discovery cohort of SP and FP ALS patients. Immunoassays were used to quantify and validate levels of the top biomarkers. A state-transition mathematical model was created using the longitudinal MS data that also predicted FP versus SP.

Results

We identified a total of 1148 proteins in the CSF of all ALS patients. Pathway analysis determined enrichment of pathways related to complement and coagulation cascades in FPs and synaptogenesis and glucose metabolism in SPs. Longitudinal analysis revealed a panel of 59 candidate markers that could segregate FP and SP ALS. Based on multivariate analysis, we identified three biomarkers (F12, RBP4, and SERPINA4) as top candidates that segregate ALS based on rate of disease progression. These proteins were validated in the discovery and a separate validation cohort. Our state-transition model determined that the overall variance of the proteome over time was predictive of the disease progression rate.

Interpretation

We identified pathways and protein biomarkers that distinguish rate of ALS disease progression. A mathematical model of the CSF proteome determined that the change in entropy of the proteome over time was predictive of FP versus SP.

Sandy coastal sediments are global hotspots for microbial mineralization of organic matter and denitrification. These sediments are characterized by advective porewater flow, tidal cycling and an active and complex microbial community. Metagenomic sequencing of microbial communities sampled from such sediments showed that potential sulfur oxidizing Gammaproteobacteria and members of the enigmatic BD1-5/SN-2 candidate phylum were abundant in situ (>10% and ~2% respectively). By mimicking the dynamic oxic/anoxic environmental conditions of the sediment in a laboratory chemostat, a simplified microbial community was selected from the more complex inoculum. Metagenomics, proteomics and fluorescence in situ hybridization showed that this simplified community contained both a potential sulfur oxidizing Gammaproteobacteria (at 24 ± 2% abundance) and a member of the BD1-5/SN-2 candidate phylum (at 7 ± 6% abundance). Despite the abundant supply of organic substrates to the chemostat, proteomic analysis suggested that the selected gammaproteobacterium grew partially autotrophically and performed hydrogen/formate oxidation. The enrichment of a member of the BD1-5/SN-2 candidate phylum enabled, for the first time, direct microscopic observation by fluorescent in situ hybridization and the experimental validation of the previously predicted translation of the stop codon UGA into glycine.

Purpose: Small cell carcinoma of the ovary, hypercalcemic type (SCCOHT) is a rare, aggressive ovarian cancer in young women that is universally driven by loss of the SWI/SNF ATPase subunits SMARCA4 and SMARCA2. A great need exists for effective targeted therapies for SCCOHT.Experimental Design: To identify underlying therapeutic vulnerabilities in SCCOHT, we conducted high-throughput siRNA and drug screens. Complementary proteomics approaches profiled kinases inhibited by ponatinib. Ponatinib was tested for efficacy in two patient-derived xenograft (PDX) models and one cell-line xenograft model of SCCOHT.Results: The receptor tyrosine kinase (RTK) family was enriched in siRNA screen hits, with FGFRs and PDGFRs being overlapping hits between drug and siRNA screens. Of multiple potent drug classes in SCCOHT cell lines, RTK inhibitors were only one of two classes with selectivity in SCCOHT relative to three SWI/SNF wild-type ovarian cancer cell lines. We further identified ponatinib as the most effective clinically approved RTK inhibitor. Reexpression of SMARCA4 was shown to confer a 1.7-fold increase in resistance to ponatinib. Subsequent proteomic assessment of ponatinib target modulation in SCCOHT cell models confirmed inhibition of nine known ponatinib target kinases alongside 77 noncanonical ponatinib targets in SCCOHT. Finally, ponatinib delayed tumor doubling time 4-fold in SCCOHT-1 xenografts while reducing final tumor volumes in SCCOHT PDX models by 58.6% and 42.5%.Conclusions: Ponatinib is an effective agent for SMARCA4-mutant SCCOHT in both in vitro and in vivo preclinical models through its inhibition of multiple kinases. Clinical investigation of this FDA-approved oncology drug in SCCOHT is warranted. Clin Cancer Res; 24(8); 1932-43. ©2018 AACR.