Coordinated proteome change precedes cell lysis and death in a mat-forming cyanobacterium.

Cyanobacteria form dense multicellular communities that experience transient conditions in terms of access to light and oxygen. These systems are productive but also undergo substantial biomass turnover through cell death, supplementing heightened heterotrophic respiration. Here we use metagenomics and metaproteomics to survey the molecular response of a mat-forming cyanobacterium undergoing mass cell lysis after exposure to dark and anoxic conditions. A lack of evidence for viral, bacterial, or eukaryotic antagonism contradicts commonly held beliefs on the causative agent for cyanobacterial death during dense growth. Instead, proteogenomics data indicated that lysis likely resulted from a genetically programmed response triggered by a failure to maintain osmotic pressure in the wake of severe energy limitation. Cyanobacterial DNA was rapidly degraded, yet cyanobacterial proteins remained abundant. A subset of proteins, including enzymes involved in amino acid metabolism, peptidases, toxin-antitoxin systems, and a potentially self-targeting CRISPR-Cas system, were upregulated upon lysis, indicating possible involvement in the programmed cell death response. We propose this natural form of cell death could provide new pathways for controlling harmful algal blooms and for sustainable bioproduct production.

Viral diversity and dynamics and CRISPR-Cas-mediated immunity in a robust alkaliphilic cyanobacterial consortium.

IMPORTANCE: Biotechnology applications utilizing the function of microbial communities have become increasingly important solutions as we strive for sustainable applications. Although viral infections are known to have a significant impact on microbial turnover and nutrient cycling, viral dynamics have remained largely overlooked in these engineered communities. Predatory perturbations to the functional stability of these microbial biotechnology applications must be investigated in order to design more robust applications. In this study, we closely examine virus-microbe dynamics in a model microbial community used in a biotechnology application. Our findings suggest that viral dynamics change significantly with environmental conditions and that microbial immunity may play an important role in maintaining functional stability. We present this study as a comprehensive template for other researchers interested in exploring predatory dynamics in engineered microbial communities.

CANT-HYD: A Curated Database of Phylogeny-Derived Hidden Markov Models for Annotation of Marker Genes Involved in Hydrocarbon Degradation.

Many pathways for hydrocarbon degradation have been discovered, yet there are no dedicated tools to identify and predict the hydrocarbon degradation potential of microbial genomes and metagenomes. Here we present the Calgary approach to ANnoTating HYDrocarbon degradation genes (CANT-HYD), a database of 37 HMMs of marker genes involved in anaerobic and aerobic degradation pathways of aliphatic and aromatic hydrocarbons. Using this database, we identify understudied or overlooked hydrocarbon degradation potential in many phyla. We also demonstrate its application in analyzing high-throughput sequence data by predicting hydrocarbon utilization in large metagenomic datasets from diverse environments. CANT-HYD is available at https://github.com/dgittins/CANT-HYD-HydrocarbonBiodegradation.

Computational approaches in viral ecology.

Dynamic virus-host interactions play a critical role in regulating microbial community structure and function. Yet for decades prior to the genomics era, viruses were largely overlooked in microbial ecology research, as only low-throughput culture-based methods of discovering viruses were available. With the advent of metagenomics, culture-independent techniques have provided exciting opportunities to discover and study new viruses. Here, we review recently developed computational methods for identifying viral sequences, exploring viral diversity in environmental samples, and predicting hosts from metagenomic sequence data. Methods to analyze viruses in silico utilize unconventional approaches to tackle challenges unique to viruses, such as vast diversity, mosaic viral genomes, and the lack of universal marker genes. As the field of viral ecology expands exponentially, computational advances have become increasingly important to gain insight into the role viruses in diverse habitats.