The denitrifying betaproteobacterium Sterolibacterium denitrificans serves as model organism for studying the oxygen-independent degradation of cholesterol. Here, we demonstrate its capability of degrading various globally abundant side chain containing zoo-, phyto- and mycosterols. We provide the complete genome that empowered an integrated genomics/proteomics/metabolomics approach, accompanied by the characterization of a characteristic enzyme of steroid side chain degradation. The results indicate that individual molybdopterin-containing steroid dehydrogenases are involved in C25-hydroxylations of steroids with different isoprenoid side chains, followed by the unusual conversion to C26-oic acids. Side chain degradation to androsta-1,4-diene-3,17-dione (ADD) via aldolytic C-C bond cleavages involves acyl-CoA synthetases/dehydrogenases specific for the respective 26-, 24- and 22-oic acids/-oyl-CoAs and promiscuous MaoC-like enoyl-CoA hydratases, aldolases and aldehyde dehydrogenases. Degradation of rings A and B depends on gene products uniquely found in anaerobic steroid degraders, which after hydrolytic cleavage of ring A, again involves CoA-ester intermediates. The degradation of the remaining CD rings via hydrolytic cleavage appears to be highly similar in aerobic and anaerobic bacteria. Anaerobic cholesterol degradation employs a composite repertoire of more than 40 genes partially known from aerobic degradation in gammaproteobacteria/actinobacteria, supplemented by unique genes that are required to circumvent oxygenase-dependent reactions.

In this study, we analyze the Genetic Analysis Workshop 17 data to identify regions of single-nucleotide polymorphisms (SNPs) that exhibit a significant influence on response rate (proportion of subjects with an affirmative affected status), called the affected ratio, among rare variants. Under the null hypothesis, the distribution of rare variants is assumed to be uniform over case (affected) and control (unaffected) subjects. We attempt to pinpoint regions where the composition is significantly different between case and control events, specifically where there are unusually high numbers of rare variants among affected subjects. We focus on private variants, which require a degree of “collapsing” to combine information over several SNPs, to obtain meaningful results. Instead of implementing a gene-based approach, where regions would vary in size and sometimes be too small to achieve a strong enough signal, we implement a fixed-bin approach, with a preset number of SNPs per region, relying on the assumption that proximity and similarity go hand in hand. Through application of 100-SNP and 30-SNP fixed bins, we identify several most influential regions, which later are seen to contain some of the causal SNPs. The 100- and 30-SNP approaches detected seven and three causal SNPs among the most significant regions, respectively, with two overlapping SNPs located in the ELAVL4 gene, reported by both procedures.

The denitrifying betaproteobacterium Chol1S catabolizes steroids such as cholesterol via an oxygen-independent pathway. It involves enzyme reaction sequences described for aerobic cholesterol and bile acid degradation as well as enzymes uniquely found in anaerobic steroid-degrading bacteria. Recent studies provided evidence that in, the cholest-4-en-3-one intermediate is oxygen-independently oxidized to Δ-dafachronic acid (C-oic acid), which is subsequently activated by a substrate-specific acyl-coenzyme A (acyl-CoA) synthetase (ACS). Further degradation was suggested to proceed via unconventional β-oxidation, where aldolases, aldehyde dehydrogenases, and additional ACSs substitute for classical β-hydroxyacyl-CoA dehydrogenases and thiolases. Here, we heterologously expressed three cholesterol-induced genes that putatively code for AMP-forming ACSs and characterized two of the products as specific 3β-hydroxy-Δ-cholenoyl-CoA (C-oic acid)- and pregn-4-en-3-one-22-oyl-CoA (C-oic acid)-forming ACSs, respectively. A third heterologously produced ATP-dependent ACS was inactive with C-, C-, or C-oic-acids but activated 3aα-H-4α-(3'propanoate)-7aβ-methylhexahydro-1,5-indanedione (HIP) to HIP-CoA, a rather late intermediate of aerobic cholesterol degradation that still contains the CD rings of the sterane skeleton. This work provides experimental evidence that anaerobic steroid degradation proceeds via numerous alternate CoA-ester-dependent or -independent enzymatic reaction sequences as a result of aldolytic side chain and hydrolytic sterane ring C-C bond cleavages. The aldolytic side chain degradation pathway comprising highly exergonic ACSs and aldehyde dehydrogenases is considered to be essential for driving the unfavorable oxygen-independent C hydroxylation forward. The biological degradation of ubiquitously abundant steroids is hampered by their low solubility and the presence of two quaternary carbon atoms. The degradation of cholesterol by aerobic has been studied in detail for more than 30 years and involves a number of oxygenase-dependent reactions. In contrast, much less is known about the oxygen-independent degradation of steroids in denitrifying bacteria. In the cholesterol-degrading anaerobic model organism Chol1S, initial evidence has been obtained that steroid degradation proceeds via numerous alternate coenzyme A (CoA)-ester-dependent/independent reaction sequences. Here, we describe the heterologous expression of three highly specific and characteristic acyl-CoA synthetases, two of which play key roles in the degradation of the side chain, whereas a third one is specifically involved in the B ring degradation. The results obtained shed light into oxygen-independent steroid degradation comprising more than 40 enzymatic reactions.

The ability to control mammalian genes in a synergistic mode using synthetic transcription factors is highly desirable in fields of tissue engineering, stem cell reprogramming and fundamental research. In this study, we developed a standardized toolkit utilizing an engineered CRISPR/Cas9 system that enables customizable gene regulation in mammalian cells. The RNA-guided dCas9 protein was implemented as a programmable transcriptional activator or repressor device, including targeting of endogenous loci. For facile assembly of single or multiple CRISPR RNAs, our toolkit comprises a modular RNAimer plasmid, which encodes the required noncoding RNA components.

It has recently become possible to identify cone photoreceptors in primate retina from multi-electrode recordings of ganglion cell spiking driven by visual stimuli of sufficiently high spatial resolution. In this paper we present a statistical approach to the problem of identifying the number, locations, and color types of the cones observed in this type of experiment. We develop an adaptive Markov Chain Monte Carlo (MCMC) method that explores the space of cone configurations, using a Linear-Nonlinear-Poisson (LNP) encoding model of ganglion cell spiking output, while analytically integrating out the functional weights between cones and ganglion cells. This method provides information about our posterior certainty about the inferred cone properties, and additionally leads to improvements in both the speed and quality of the inferred cone maps, compared to earlier “greedy” computational approaches.

The microbial production of methane from organic matter is an essential process in the global carbon cycle and an important source of renewable energy. It involves the syntrophic interaction between methanogenic archaea and bacteria that convert primary fermentation products such as fatty acids to the methanogenic substrates acetate, H2, CO2, or formate. While the concept of syntrophic methane formation was developed half a century ago, the highly endergonic reduction of CO2 to methane by electrons derived from β-oxidation of saturated fatty acids has remained hypothetical. Here, we studied a previously noncharacterized membrane-bound oxidoreductase (EMO) from Syntrophus aciditrophicus containing two heme b cofactors and 8-methylmenaquinone as key redox components of the redox loop–driven reduction of CO2 by acyl–coenzyme A (CoA). Using solubilized EMO and proteoliposomes, we reconstituted the entire electron transfer chain from acyl-CoA to CO2 and identified the transfer from a high- to a low-potential heme b with perfectly adjusted midpoint potentials as key steps in syntrophic fatty acid oxidation. The results close our gap of knowledge in the conversion of biomass into methane and identify EMOs as key players of β-oxidation in (methyl)menaquinone-containing organisms.

In this study, we analyze the Genetic Analysis Workshop 18 (GAW18) data to identify regions of single-nucleotide polymorphisms (SNPs), which significantly influence hypertension status among individuals. We have studied the marginal impact of these regions on disease status in the past, but we extend the method to deal with environmental factors present in data collected over several exam periods. We consider the respective interactions between such traits as smoking status and age with the genetic information and hope to augment those genetic regions deemed influential marginally with those that contribute via an interactive effect. In particular, we focus only on rare variants and apply a procedure to combine signal among rare variants in a number of "fixed bins" along the chromosome. We extend the procedure in Agne et al [1] to incorporate environmental factors by dichotomizing subjects via traits such as smoking status and age, running the marginal procedure among each respective category (i.e., smokers or nonsmokers), and then combining their scores into a score for interaction. To avoid overlap of subjects, we examine each exam period individually. Out of a possible 629 fixed-bin regions in chromosome 3, we observe that 11 show up in multiple exam periods for gene-smoking score. Fifteen regions exhibit significance for multiple exam periods for gene-age score, with 4 regions deemed significant for all 3 exam periods. The procedure pinpoints SNPs in 8 "answer" genes, with 5 of these showing up as significant in multiple testing schemes (Gene-Smoking, Gene-Age for Exams 1, 2, and 3).

We propose a new method for identifying disease-related regions of single nucleotide variants in recently admixed populations. We use principal component analysis to derive both global and local ancestry information. We then use the summation partition approach to search for disease-related regions based on both rare variants and the local ancestral information of each region. We demonstrate this method using individuals with high systolic blood pressure from a sample of unrelated Mexican American subjects provided in the 19th Genetic Analysis Workshop.