Paul E. Abraham

Proteogenomic Monitoring of Geobacter Physiology during Stimulated Uranium Bioremediation

ABSTRACT Implementation of uranium bioremediation requires methods for monitoring the membership and activities of the subsurface microbial communities that are responsible for reduction of soluble U(VI) to insoluble U(IV). Here, we report a proteomics-based approach for simultaneously documenting the strain membership and microbial physiology of the dominant Geobacter community members during in situ acetate amendment of the U-contaminated Rifle, CO, aquifer. Three planktonic Geobacter-dominated samples were obtained from two wells down-gradient of acetate addition. Over 2,500 proteins from each of these samples were identified by matching liquid chromatography-tandem mass spectrometry spectra to peptides predicted from seven isolate Geobacter genomes. Genome-specific peptides indicate early proliferation of multiple M21 and Geobacter bemidjiensis-like strains and later possible emergence of M21 and G. bemidjiensis-like strains more closely related to Geobacter lovleyi. Throughout biostimulation, the proteome is dominated by enzymes that convert acetate to acetyl-coenzyme A and pyruvate for central metabolism, while abundant peptides matching tricarboxylic acid cycle proteins and ATP synthase subunits were also detected, indicating the importance of energy generation during the period of rapid growth following the start of biostimulation. Evolving Geobacter strain composition may be linked to changes in protein abundance over the course of biostimulation and may reflect changes in metabolic functioning. Thus, metagenomics-independent community proteogenomics can be used to diagnose the status of the subsurface consortia upon which remediation biotechnology relies.

Environmental proteomics of microbial plankton in a highly productive coastal upwelling system

Metaproteomics is one of a suite of new approaches providing insights into the activities of microorganisms in natural environments. Proteins, the final products of gene expression, indicate cellular priorities, taking into account both transcriptional and posttranscriptional control mechanisms that control adaptive responses. Here, we report the proteomic composition of the < 1.2 μm fraction of a microbial community from Oregon coast summer surface waters, detected with two-dimensional liquid chromatography coupled with electrospray tandem mass spectrometry. Spectra corresponding to proteins involved in protein folding and biosynthesis, transport, and viral capsid structure were the most frequently detected. A total of 36% of all the detected proteins were best matches to the SAR11 clade, and other abundant coastal microbial clades were also well represented, including the Roseobacter clade (17%), oligotrophic marine gammaproteobacteria group (6%), OM43 clade (1%). Viral origins were attributed to 2.5% of proteins. In contrast to oligotrophic waters, phosphate transporters were not highly detected in this nutrient-rich system. However, transporters for amino acids, taurine, polyamines and glutamine synthetase were among the most highly detected proteins, supporting predictions that carbon and nitrogen are more limiting than phosphate in this environment. Intriguingly, one of the highly detected proteins was methanol dehydrogenase originating from the OM43 clade, providing further support for recent reports that the metabolism of one-carbon compounds by these streamlined methylotrophs might be an important feature of coastal ocean biogeochemistry.

Discovery and annotation of small proteins using genomics, proteomics, and computational approaches

Small proteins (10-200 amino acids [aa] in length) encoded by short open reading frames (sORF) play important regulatory roles in various biological processes, including tumor progression, stress response, flowering, and hormone signaling. However, ab initio discovery of small proteins has been relatively overlooked. Recent advances in deep transcriptome sequencing make it possible to efficiently identify sORFs at the genome level. In this study, we obtained ~2.6 million expressed sequence tag (EST) reads from Populus deltoides leaf transcriptome and reconstructed full-length transcripts from the EST sequences. We identified an initial set of 12,852 sORFs encoding proteins of 10-200 aa in length. Three computational approaches were then used to enrich for bona fide protein-coding sORFs from the initial sORF set: (1) coding-potential prediction, (2) evolutionary conservation between P. deltoides and other plant species, and (3) gene family clustering within P. deltoides. As a result, a high-confidence sORF candidate set containing 1469 genes was obtained. Analysis of the protein domains, non-protein-coding RNA motifs, sequence length distribution, and protein mass spectrometry data supported this high-confidence sORF set. In the high-confidence sORF candidate set, known protein domains were identified in 1282 genes (higher-confidence sORF candidate set), out of which 611 genes, designated as highest-confidence candidate sORF set, were supported by proteomics data. Of the 611 highest-confidence candidate sORF genes, 56 were new to the current Populus genome annotation. This study not only demonstrates that there are potential sORF candidates to be annotated in sequenced genomes, but also presents an efficient strategy for discovery of sORFs in species with no genome annotation yet available.

A roadmap for research on crassulacean acid metabolism (CAM) to enhance sustainable food and bioenergy production in a hotter, drier world

Crassulacean acid metabolism (CAM) is a specialized mode of photosynthesis that features nocturnal CO2 uptake, facilitates increased water-use efficiency (WUE), and enables CAM plants to inhabit water-limited environments such as semi-arid deserts or seasonally dry forests. Human population growth and global climate change now present challenges for agricultural production systems to increase food, feed, forage, fiber, and fuel production. One approach to meet these challenges is to increase reliance on CAM crops, such as Agave and Opuntia, for biomass production on semi-arid, abandoned, marginal, or degraded agricultural lands. Major research efforts are now underway to assess the productivity of CAM crop species and to harness the WUE of CAM by engineering this pathway into existing food, feed, and bioenergy crops. An improved understanding of CAM has potential for high returns on research investment. To exploit the potential of CAM crops and CAM bioengineering, it will be necessary to elucidate the evolution, genomic features, and regulatory mechanisms of CAM. Field trials and predictive models will be required to assess the productivity of CAM crops, while new synthetic biology approaches need to be developed for CAM engineering. Infrastructure will be needed for CAM model systems, field trials, mutant collections, and data management.

Microbial metaproteomics for characterizing the range of metabolic functions and activities of human gut microbiota

The human gastrointestinal tract is a complex, dynamic ecosystem that consists of a carefully tuned balance of human host and microbiota membership. The microbiome is not merely a collection of opportunistic parasites, but rather provides important functions to the host that are absolutely critical to many aspects of health, including nutrient transformation and absorption, drug metabolism, pathogen defense, and immune system development. Microbial metaproteomics provides the ability to characterize the human gut microbiota functions and metabolic activities at a remarkably deep level, revealing information about microbiome development and stability as well as their interactions with their human host. Generally, microbial and human proteins can be extracted and then measured by high performance MS‐based proteomics technology. Here, we review the field of human gut microbiome metaproteomics, with a focus on the experimental and informatics considerations involved in characterizing systems ranging from low‐complexity model gut microbiota in gnotobiotic mice, to the emerging gut microbiome in the GI tract of newborn human infants, and finally to an established gut microbiota in human adults.

Defining the Boundaries and Characterizing the Landscape of Functional Genome Expression in Vascular Tissues of Populus using Shotgun Proteomics

Current state-of-the-art experimental and computational proteomic approaches were integrated to obtain a comprehensive protein profile of Populus vascular tissue. This featured: (1) a large sample set consisting of two genotypes grown under normal and tension stress conditions, (2) bioinformatics clustering to effectively handle gene duplication, and (3) an informatics approach to track and identify single amino acid polymorphisms (SAAPs). By applying a clustering algorithm to the Populus database, the number of protein entries decreased from 64,689 proteins to a total of 43,069 protein groups, thereby reducing 7505 identified proteins to a total of 4226 protein groups, in which 2016 were singletons. This reduction implies that ∼50% of the measured proteins shared extensive sequence homology. Using conservative search criteria, we were able to identify 1354 peptides containing a SAAP and 201 peptides that become tryptic due to a K or R substitution. These newly identified peptides correspond to 502 proteins, including 97 previously unidentified proteins. In total, the integration of deep proteome measurements on an extensive sample set with protein clustering and peptide sequence variants provided an exceptional level of proteome characterization for Populus, allowing us to spatially resolve the vascular tissue proteome.

Transcript, protein and metabolite temporal dynamics in the CAM plant Agave

Already a proven mechanism for drought resilience, crassulacean acid metabolism (CAM) is a specialized type of photosynthesis that maximizes water-use efficiency by means of an inverse (compared to C3 and C4 photosynthesis) day/night pattern of stomatal closure/opening to shift CO2 uptake to the night, when evapotranspiration rates are low. A systems-level understanding of temporal molecular and metabolic controls is needed to define the cellular behaviour underpinning CAM. Here, we report high-resolution temporal behaviours of transcript, protein and metabolite abundances across a CAM diel cycle and, where applicable, compare the observations to the well-established C3 model plant Arabidopsis. A mechanistic finding that emerged is that CAM operates with a diel redox poise that is shifted relative to that in Arabidopsis. Moreover, we identify widespread rescheduled expression of genes associated with signal transduction mechanisms that regulate stomatal opening/closing. Controlled production and degradation of transcripts and proteins represents a timing mechanism by which to regulate cellular function, yet knowledge of how this molecular timekeeping regulates CAM is unknown. Here, we provide new insights into complex post-transcriptional and -translational hierarchies that govern CAM in Agave. These data sets provide a resource to inform efforts to engineer more efficient CAM traits into economically valuable C3 crops.

Impact of Phenolic Substrate and Growth Temperature on the Arthrobacter chlorophenolicus Proteome

We compared the Arthrobacter chlorophenolicus proteome during growth on 4-chlorophenol, 4-nitrophenol, or phenol at 5 and 28 degrees C, both for the wild-type and a mutant strain with mass spectrometry based proteomics. A label-free workflow employing spectral counting identified 3749 proteins across all growth conditions, representing over 70% of the predicted genome and 739 of these proteins form the core proteome. Statistically significant differences were found in the proteomes of cells grown under different conditions including differentiation of hundreds of unknown proteins. The 4-chlorophenol-degradation pathway was confirmed, but not that for phenol.

Metaproteomics: extracting and mining proteome information to characterize metabolic activities in microbial communities

Contemporary microbial ecology studies usually employ one or more “omics” approaches to investigate the structure and function of microbial communities. Among these, metaproteomics aims to characterize the metabolic activities of the microbial membership, providing a direct link between the genetic potential and functional metabolism. The successful deployment of metaproteomics research depends on the integration of high‐quality experimental and bioinformatic techniques for uncovering the metabolic activities of a microbial community in a way that is complementary to other “meta‐omic” approaches. The essential, quality‐defining informatics steps in metaproteomics investigations are: (1) construction of the metagenome, (2) functional annotation of predicted protein‐coding genes, (3) protein database searching, (4) protein inference, and (5) extraction of metabolic information. In this article, we provide an overview of current bioinformatic approaches and software implementations in metaproteome studies in order to highlight the key considerations needed for successful implementation of this powerful community‐biology tool. Curr. Protoc. Bioinform. 46:13.26.1‐13.26.14.

Eliminating a global regulator of carbon catabolite repression enhances the conversion of aromatic lignin monomers to muconate in Pseudomonas putida KT2440

Carbon catabolite repression refers to the preference of microbes to metabolize certain growth substrates over others in response to a variety of regulatory mechanisms. Such preferences are important for the fitness of organisms in their natural environments, but may hinder their performance as domesticated microbial cell factories. In a Pseudomonas putida KT2440 strain engineered to convert lignin-derived aromatic monomers such as p-coumarate and ferulate to muconate, a precursor to bio-based nylon and other chemicals, metabolic intermediates including 4-hydroxybenzoate and vanillate accumulate and subsequently reduce productivity. We hypothesized that these metabolic bottlenecks may be, at least in part, the effect of carbon catabolite repression caused by glucose or acetate, more preferred substrates that must be provided to the strain for supplementary energy and cell growth. Using mass spectrometry-based proteomics, we have identified the 4-hydroxybenzoate hydroxylase, PobA, and the vanillate demethylase, VanAB, as targets of the Catabolite Repression Control (Crc) protein, a global regulator of carbon catabolite repression. By deleting the gene encoding Crc from this strain, the accumulation of 4-hydroxybenzoate and vanillate are reduced and, as a result, muconate production is enhanced. In cultures grown on glucose, the yield of muconate produced from p-coumarate after 36 h was increased nearly 70% with deletion of the gene encoding Crc (94.6 ± 0.6% vs. 56.0 ± 3.0% (mol/mol)) while the yield from ferulate after 72 h was more than doubled (28.3 ± 3.3% vs. 12.0 ± 2.3% (mol/mol)). The effect of eliminating Crc was similar in cultures grown on acetate, with the yield from p-coumarate just slightly higher in the Crc deletion strain after 24 h (47.7 ± 0.6% vs. 40.7 ± 3.6% (mol/mol)) and the yield from ferulate increased more than 60% after 72 h (16.9 ± 1.4% vs. 10.3 ± 0.1% (mol/mol)). These results are an example of the benefit that reducing carbon catabolite repression can have on conversion of complex feedstocks by microbial cell factories, a concept we posit could be broadly considered as a strategy in metabolic engineering for conversion of renewable feedstocks to value-added chemicals.