ß-Oxidation and autophagy are critical energy providers during acute glucose depletion in Saccharomyces cerevisiae.

The ability to tolerate and thrive in diverse environments is paramount to all living organisms, and many organisms spend a large part of their lifetime in starvation. Upon acute glucose starvation, yeast cells undergo drastic physiological and metabolic changes and reestablish a constant-although lower-level of energy production within minutes. The molecules that are rapidly metabolized to fuel energy production under these conditions are unknown. Here, we combine metabolomics and genetics to characterize the cells' response to acute glucose depletion and identify pathways that ensure survival during starvation. We show that the ability to respire is essential for maintaining the energy status and to ensure viability during starvation. Measuring the cells' immediate metabolic response, we find that central metabolites drastically deplete and that the intracellular AMP-to-ATP ratio strongly increases within 20 to 30 s. Furthermore, we detect changes in both amino acid and lipid metabolite levels. Consistent with this, both bulk autophagy, a process that frees amino acids, and lipid degradation via ß-oxidation contribute in parallel to energy maintenance upon acute starvation. In addition, both these pathways ensure long-term survival during starvation. Thus, our results identify bulk autophagy and ß-oxidation as important energy providers during acute glucose starvation.

Expression Dysregulation as a Mediator of Fitness Costs in Antibiotic Resistance.

Antimicrobial resistance (AMR) poses a threat to global health and the economy. Rifampicin-resistant Mycobacterium tuberculosis accounts for a third of the global AMR burden. Gaining the upper hand on AMR requires a deeper understanding of the physiology of resistance. AMR often results in a fitness cost in the absence of drug. Identifying the molecular mechanisms underpinning this cost could help strengthen future treatment regimens. Here, we used a collection of M. tuberculosis strains that provide an evolutionary and phylogenetic snapshot of rifampicin resistance and subjected them to genome-wide transcriptomic and proteomic profiling to identify key perturbations of normal physiology. We found that the clinically most common rifampicin resistance-conferring mutation, RpoB Ser450Leu, imparts considerable gene expression changes, many of which are mitigated by the compensatory mutation in RpoC Leu516Pro. However, our data also provide evidence for pervasive epistasis-the same resistance mutation imposed a different fitness cost and functionally distinct changes to gene expression in genetically unrelated clinical strains. Finally, we report a likely posttranscriptional modulation of gene expression that is shared in most of the tested strains carrying RpoB Ser450Leu, resulting in an increased abundance of proteins involved in central carbon metabolism. These changes contribute to a more general trend in which the disruption of the composition of the proteome correlates with the fitness cost of the RpoB Ser450Leu mutation in different strains.

SLAW: A Scalable and Self-Optimizing Processing Workflow for Untargeted LC-MS.

Metabolomics has been shown to be promising for diverse applications in basic, applied, and clinical research. These applications often require large-scale data, and while the technology to perform such experiments exists, downstream analysis remains challenging. Different tools exist in a variety of ecosystems, but they often do not scale to large data and are not integrated into a single coherent workflow. Moreover, the outcome of processing is very sensitive to a multitude of algorithmic parameters. Hence, parameter optimization is not only critical but also challenging. We present SLAW, a scalable and yet easy-to-use workflow for processing untargeted LC-MS data in metabolomics and lipidomics. The capabilities of SLAW include (1) state-of-the-art peak-picking algorithms, (2) a new automated parameter optimization routine, (3) an efficient sample alignment procedure, (4) gap filling by data recursion, and (5) the extraction of consolidated MS2 and an isotopic pattern across all samples. Importantly, both the workflow and the parameter optimization were designed for robust analysis of untargeted studies with thousands of individual LC-MSn runs. We compared SLAW to two state-of-the-art workflows based on openMS and XCMS. SLAW was able to detect and align more reproducible features in all data sets considered. SLAW scaled well, and its analysis of a data set with 2500 LC-MS files consumed 40% less memory and was 6 times faster than that using the XCMS-based workflow. SLAW also extracted 2-fold more isotopic patterns and MS2 spectra, which in 60% of the cases led to positive matches against a spectral library.

Membrane composition and organization of Bacillus subtilis 168 and its genome-reduced derivative miniBacillus PG10.

A form of lateral membrane compartmentalization in bacteria is represented by functional membrane microdomains (FMMs). FMMs are important for various cellular processes and offer application possibilities in microbial biotechnology. We designed a lipidomics method to directly measure relative abundances of lipids in detergent-resistant and detergent-sensitive membrane fractions of the model bacterium Bacillus subtilis 168 and the biotechnologically attractive miniBacillus PG10 strain. Our study supports previous work suggesting that cardiolipin and prenol lipids are enriched in FMMs of B. subtilis. Additionally, structural analysis of acyl chains of major phospholipids indicated that FMMs display increased order and thickness compared with the surrounding bilayer. Despite the 36% genome reduction, membrane and FMM integrity are largely preserved in miniBacillus PG10, as supported by analysis of membrane fluidity, flotillin distribution and gene expression data. The novel insights in FMM architecture reported here will contribute to further explore the biological significance of FMMs and the means by which FMMs can be exploited as heterologous production platforms. Moreover, our lipidomics method enables comparative FMM lipid profiling between different bacteria.

Modularized CRISPR/dCas9 effector toolkit for target-specific gene regulation.

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.