Proteomic and metabolic disturbances in lignin-modified Brachypodium distachyon.

Lignin biosynthesis begins with the deamination of phenylalanine and tyrosine (Tyr) as a key branch point between primary and secondary metabolism in land plants. Here, we used a systems biology approach to investigate the global metabolic responses to lignin pathway perturbations in the model grass Brachypodium distachyon. We identified the lignin biosynthetic protein families and found that ammonia-lyases (ALs) are among the most abundant proteins in lignifying tissues in grasses. Integrated metabolomic and proteomic data support a link between lignin biosynthesis and primary metabolism mediated by the ammonia released from ALs that is recycled for the synthesis of amino acids via glutamine. RNA interference knockdown of lignin genes confirmed that the route of the canonical pathway using shikimate ester intermediates is not essential for lignin formation in Brachypodium, and there is an alternative pathway from Tyr via sinapic acid for the synthesis of syringyl lignin involving yet uncharacterized enzymatic steps. Our findings support a model in which plant ALs play a central role in coordinating the allocation of carbon for lignin synthesis and the nitrogen available for plant growth. Collectively, these data also emphasize the value of integrative multiomic analyses to advance our understanding of plant metabolism.

Profiling Protein-Protein Interactions in the Human Brain by Refined Cofractionation Mass Spectrometry.

Proteins usually execute their biological functions through interactions with other proteins and by forming macromolecular complexes, but global profiling of protein complexes directly from human tissue samples has been limited. In this study, we utilized cofractionation mass spectrometry (CF-MS) to map protein complexes within the postmortem human brain with experimental replicates. First, we used concatenated anion and cation Ion Exchange Chromatography (IEX) to separate native protein complexes in 192 fractions and then proceeded with Data-Independent Acquisition (DIA) mass spectrometry to analyze the proteins in each fraction, quantifying a total of 4,804 proteins with 3,260 overlapping in both replicates. We improved the DIA's quantitative accuracy by implementing a constant amount of bovine serum albumin (BSA) in each fraction as an internal standard. Next, advanced computational pipelines, which integrate both a database-based complex analysis and an unbiased protein-protein interaction (PPI) search, were applied to identify protein complexes and construct protein-protein interaction networks in the human brain. Our study led to the identification of 486 protein complexes and 10054 binary protein-protein interactions, which represents the first global profiling of human brain PPIs using CF-MS. Overall, this study offers a resource and tool for a wide range of human brain research, including the identification of disease-specific protein complexes in the future.

Expression quantitative trait loci mapping identified PtrXB38 as a key hub gene in adventitious root development in Populus.

Plant establishment requires the formation and development of an extensive root system with architecture modulated by complex genetic networks. Here, we report the identification of the PtrXB38 gene as an expression quantitative trait loci (eQTL) hotspot, mapped using 390 leaf and 444 xylem Populus trichocarpa transcriptomes. Among predicted targets of this trans-eQTL were genes involved in plant hormone responses and root development. Overexpression of PtrXB38 in Populus led to significant increases in callusing and formation of both stem-born roots and base-born adventitious roots. Omics studies revealed that genes and proteins controlling auxin transport and signaling were involved in PtrXB38-mediated adventitious root formation. Protein-protein interaction assays indicated that PtrXB38 interacts with components of endosomal sorting complexes required for transport machinery, implying that PtrXB38-regulated root development may be mediated by regulating endocytosis pathway. Taken together, this work identified a crucial root development regulator and sheds light on the discovery of other plant developmental regulators through combining eQTL mapping and omics approaches.

Bacterial Homologs of Progestin and AdipoQ Receptors (PAQRs) Affect Membrane Energetics Homeostasis but Not Fluidity.

Membrane potential homeostasis is essential for cell survival. Defects in membrane potential lead to pleiotropic phenotypes, consistent with the central role of membrane energetics in cell physiology. Homologs of the progestin and AdipoQ receptors (PAQRs) are conserved in multiple phyla of Bacteria and Eukarya. In eukaryotes, PAQRs are proposed to modulate membrane fluidity and fatty acid (FA) metabolism. The role of bacterial homologs has not been elucidated. Here, we use Escherichia coli and Bacillus subtilis to show that bacterial PAQR homologs, which we name "TrhA," have a role in membrane energetics homeostasis. Using transcriptional fusions, we show that E. coli TrhA (encoded by yqfA) is part of the unsaturated fatty acid biosynthesis regulon. Fatty acid analyses and physiological assays show that a lack of TrhA in both E. coli and B. subtilis (encoded by yplQ) provokes subtle but consistent changes in membrane fatty acid profiles that do not translate to control of membrane fluidity. Instead, membrane proteomics in E. coli suggested a disrupted energy metabolism and dysregulated membrane energetics in the mutant, though it grew similarly to its parent. These changes translated into a disturbed membrane potential in the mutant relative to its parent under various growth conditions. Similar dysregulation of membrane energetics was observed in a different E. coli strain and in the distantly related B. subtilis. Together, our findings are consistent with a role for TrhA in membrane energetics homeostasis, through a mechanism that remains to be elucidated. IMPORTANCE Eukaryotic homologs of the progestin and AdipoQ receptor family (PAQR) have been shown to regulate membrane fluidity by affecting, through unknown mechanisms, unsaturated fatty acid (FA) metabolism. The bacterial homologs studied here mediate small and consistent changes in unsaturated FA metabolism that do not seem to impact membrane fluidity but, rather, alter membrane energetics homeostasis. Together, the findings here suggest that bacterial and eukaryotic PAQRs share functions in maintaining membrane homeostasis (fluidity in eukaryotes and energetics for bacteria with TrhA homologs).

Temporal dynamics of protein and post-translational modification abundances in Populus leaf across a diurnal period.

Populus spp. are dedicated woody biomass feedstocks for advanced biofuels and bioproducts. Proper growth and fitness of poplar as a sustainable feedstock depends on timely perception and response to environmental signals (e.g., light, temperature, water). Poplar leaves, like other C3 photosynthesis plants, have evolved oscillating or circadian rhythms that play important roles in synchronizing biological processes with external cues. To characterize this phenomenon at a molecular level, we employed bottom-up proteomics using high-resolution mass spectrometry and de novo-assisted database searching to identify abundance changes in proteins and post-translational modifications in poplar leaf tissue sampled across a 12/12-hour light/dark diurnal period.

Towards engineering ectomycorrhization into switchgrass bioenergy crops via a lectin receptor-like kinase.

Soil-borne microbes can establish compatible relationships with host plants, providing a large variety of nutritive and protective compounds in exchange for photosynthesized sugars. However, the molecular mechanisms mediating the establishment of these beneficial relationships remain unclear. Our previous genetic mapping and whole-genome resequencing studies identified a gene deletion event of a Populus trichocarpa lectin receptor-like kinase gene PtLecRLK1 in Populus deltoides that was associated with poor-root colonization by the ectomycorrhizal fungus Laccaria bicolor. By introducing PtLecRLK1 into a perennial grass known to be a non-host of L. bicolor, switchgrass (Panicum virgatum L.), we found that L. bicolor colonizes ZmUbipro-PtLecRLK1 transgenic switchgrass roots, which illustrates that the introduction of PtLecRLK1 has the potential to convert a non-host to a host of L. bicolor. Furthermore, transcriptomic and proteomic analyses on inoculated-transgenic switchgrass roots revealed genes/proteins overrepresented in the compatible interaction and underrepresented in the pathogenic defence pathway, consistent with the view that pathogenic defence response is down-regulated during compatible interaction. Metabolomic profiling revealed that root colonization in the transgenic switchgrass was associated with an increase in N-containing metabolites and a decrease in organic acids, sugars, and aromatic hydroxycinnamate conjugates, which are often seen in the early steps of establishing compatible interactions. These studies illustrate that PtLecRLK1 is able to render a plant susceptible to colonization by the ectomycorrhizal fungus L. bicolor and shed light on engineering mycorrhizal symbiosis into a non-host to enhance plant productivity and fitness on marginal lands.

Metaproteomics reveals insights into microbial structure, interactions, and dynamic regulation in defined communities as they respond to environmental disturbance.

BACKGROUND: Microbe-microbe interactions between members of the plant rhizosphere are important but remain poorly understood. A more comprehensive understanding of the molecular mechanisms used by microbes to cooperate, compete, and persist has been challenging because of the complexity of natural ecosystems and the limited control over environmental factors. One strategy to address this challenge relies on studying complexity in a progressive manner, by first building a detailed understanding of relatively simple subsets of the community and then achieving high predictive power through combining different building blocks (e.g., hosts, community members) for different environments. Herein, we coupled this reductionist approach with high-resolution mass spectrometry-based metaproteomics to study molecular mechanisms driving community assembly, adaptation, and functionality for a defined community of ten taxonomically diverse bacterial members of Populus deltoides rhizosphere co-cultured either in a complex or defined medium. RESULTS: Metaproteomics showed this defined community assembled into distinct microbiomes based on growth media that eventually exhibit composition and functional stability over time. The community grown in two different media showed variation in composition, yet both were dominated by only a few microbial strains. Proteome-wide interrogation provided detailed insights into the functional behavior of each dominant member as they adjust to changing community compositions and environments. The emergence and persistence of select microbes in these communities were driven by specialization in strategies including motility, antibiotic production, altered metabolism, and dormancy. Protein-level interrogation identified post-translational modifications that provided additional insights into regulatory mechanisms influencing microbial adaptation in the changing environments. CONCLUSIONS: This study provides high-resolution proteome-level insights into our understanding of microbe-microbe interactions and highlights specialized biological processes carried out by specific members of assembled microbiomes to compete and persist in changing environmental conditions. Emergent properties observed in these lower complexity communities can then be re-evaluated as more complex systems are studied and, when a particular property becomes less relevant, higher-order interactions can be identified.

A Viable New Strategy for the Discovery of Peptide Proteolytic Cleavage Products in Plant-Microbe Interactions.

Small peptides that are proteolytic cleavage products (PCPs) of less than 100 amino acids are emerging as key signaling molecules that mediate cell-to-cell communication and biological processes that occur between and within plants, fungi, and bacteria. Yet, the discovery and characterization of these molecules is largely overlooked. Today, selective enrichment and subsequent characterization by mass spectrometry-based sequencing offers the greatest potential for their comprehensive characterization, however qualitative and quantitative performance metrics are rarely captured. Herein, we addressed this need by benchmarking the performance of an enrichment strategy, optimized specifically for small PCPs, using state-of-the-art de novo-assisted peptide sequencing. As a case study, we implemented this approach to identify PCPs from different root and foliar tissues of the hybrid poplar Populus × canescens 717-1B4 in interaction with the ectomycorrhizal basidiomycete Laccaria bicolor. In total, we identified 1,660 and 2,870 Populus and L. bicolor unique PCPs, respectively. Qualitative results supported the identification of well-known PCPs, like the mature form of the photosystem II complex 5-kDa protein (approximately 3 kDa). A total of 157 PCPs were determined to be significantly more abundant in root tips with established ectomycorrhiza when compared with root tips without established ectomycorrhiza and extramatrical mycelium of L. bicolor. These PCPs mapped to 64 Populus proteins and 69 L. bicolor proteins in our database, with several of them previously implicated in biologically relevant associations between plant and fungus.

Profiling Mouse Brain Single-Cell-Type Proteomes Via Adeno-Associated Virus-Mediated Proximity Labeling and Mass Spectrometry.

Single-cell-type proteomics is an emerging field of research that combines cell-type specificity with the comprehensive proteome coverage offered by bulk proteomics. However, the extraction of single-cell-type proteomes remains a challenge, particularly for hard-to-isolate cells like neurons. In this chapter, we present an innovative technique for profiling single-cell-type proteomes using adeno-associated virus (AAV)-mediated proximity labeling (PL) and tandem-mass-tag (TMT) mass spectrometry. This technique eliminates the need for cell isolation and offers a streamlined workflow, including AAV delivery to express TurboID (an engineered biotin ligase) controlled by cell-type-specific promoters, biotinylated protein purification, on-bead digestion, TMT labeling, and liquid chromatography-mass spectrometry (LC-MS). We examined this method by analyzing distinct brain cell types in mice. Initially, recombinant AAVs were used to concurrently express TurboID and mCherry proteins driven by neuron- or astrocyte-specific promoters, which was validated through co-immunostaining with cellular markers. With biotin purification and TMT analysis, we successfully identified around 10,000 unique proteins from a few micrograms of protein samples with high reproducibility. Our statistical analyses revealed that these proteomes encompass cell-type-specific cellular pathways. By utilizing this technique, researchers can explore the proteomic landscape of specific cell types, paving the way for new insights into cellular processes, deciphering disease mechanisms, and identifying therapeutic targets in neuroscience and beyond.

The Promises, Challenges, and Opportunities of Omics for Studying the Plant Holobiont.

Microorganisms are critical drivers of biological processes that contribute significantly to plant sustainability and productivity. In recent years, emerging research on plant holobiont theory and microbial invasion ecology has radically transformed how we study plant-microbe interactions. Over the last few years, we have witnessed an accelerating pace of advancements and breadth of questions answered using omic technologies. Herein, we discuss how current state-of-the-art genomics, transcriptomics, proteomics, and metabolomics techniques reliably transcend the task of studying plant-microbe interactions while acknowledging existing limitations impeding our understanding of plant holobionts.

Meta-omics-aided isolation of an elusive anaerobic arsenic-methylating soil bacterium.

Soil microbiomes harbour unparalleled functional and phylogenetic diversity. However, extracting isolates with a targeted function from complex microbiomes is not straightforward, particularly if the associated phenotype does not lend itself to high-throughput screening. Here, we tackle the methylation of arsenic (As) in anoxic soils. As methylation was proposed to be catalysed by sulfate-reducing bacteria. However, to date, there are no available anaerobic isolates capable of As methylation, whether sulfate-reducing or otherwise. The isolation of such a microorganism has been thwarted by the fact that the anaerobic bacteria harbouring a functional arsenite S-adenosylmethionine methyltransferase (ArsM) tested to date did not methylate As in pure culture. Additionally, fortuitous As methylation can result from the release of non-specific methyltransferases upon lysis. Thus, we combined metagenomics, metatranscriptomics, and metaproteomics to identify the microorganisms actively methylating As in anoxic soil-derived microbial cultures. Based on the metagenome-assembled genomes of microorganisms expressing ArsM, we isolated Paraclostridium sp. strain EML, which was confirmed to actively methylate As anaerobically. This work is an example of the application of meta-omics to the isolation of elusive microorganisms.

Morphine and high-fat diet differentially alter the gut microbiota composition and metabolic function in lean versus obese mice.

There are known associations between opioids, obesity, and the gut microbiome, but the molecular connection/mediation of these relationships is not understood. To better clarify the interplay of physiological, genetic, and microbial factors, this study investigated the microbiome and host inflammatory responses to chronic opioid administration in genetically obese, diet-induced obese, and lean mice. Samples of feces, urine, colon tissue, and plasma were analyzed using targeted LC-MS/MS quantification of metabolites, immunoassays of inflammatory cytokine levels, genome-resolved metagenomics, and metaproteomics. Genetic obesity, diet-induced obesity, and morphine treatment in lean mice each showed increases in distinct inflammatory cytokines. Metagenomic assembly and binning uncovered over 400 novel gut bacterial genomes and species. Morphine administration impacted the microbiome's composition and function, with the strongest effect observed in lean mice. This microbiome effect was less pronounced than either diet or genetically driven obesity. Based on inferred microbial physiology from the metaproteome datasets, a high-fat diet transitioned constituent microbes away from harvesting diet-derived nutrients and towards nutrients present in the host mucosal layer. Considered together, these results identified novel host-dependent phenotypes, differentiated the effects of genetic obesity versus diet induced obesity on gut microbiome composition and function, and showed that chronic morphine administration altered the gut microbiome.

Multi-omic characterization of bifunctional peroxidase 4-coumarate 3-hydroxylase knockdown in Brachypodium distachyon provides insights into lignin modification-associated pleiotropic effects.

A bifunctional peroxidase enzyme, 4-coumarate 3-hydroxylase (C3H/APX), provides a parallel route to the shikimate shunt pathway for the conversion of 4-coumarate to caffeate in the early steps of lignin biosynthesis. Knockdown of C3H/APX (C3H/APX-KD) expression has been shown to reduce the lignin content in Brachypodium distachyon. However, like many other lignin-modified plants, C3H/APX-KDs show unpredictable pleiotropic phenotypes, including stunted growth, delayed senescence, and reduced seed yield. A system-wide level understanding of altered biological processes in lignin-modified plants can help pinpoint the lignin-modification associated growth defects to benefit future studies aiming to negate the yield penalty. Here, a multi-omic approach was used to characterize molecular changes resulting from C3H/APX-KD associated lignin modification and negative growth phenotype in Brachypodium distachyon. Our findings demonstrate that C3H/APX knockdown in Brachypodium stems substantially alters the abundance of enzymes implicated in the phenylpropanoid biosynthetic pathway and disrupt cellular redox homeostasis. Moreover, it elicits plant defense responses associated with intracellular kinases and phytohormone-based signaling to facilitate growth-defense trade-offs. A deeper understanding along with potential targets to mitigate the pleiotropic phenotypes identified in this study could aid to increase the economic feasibility of lignocellulosic biofuel production.

Bioprospecting Trichoderma: A Systematic Roadmap to Screen Genomes and Natural Products for Biocontrol Applications.

Natural products derived from microbes are crucial innovations that would help in reaching sustainability development goals worldwide while achieving bioeconomic growth. Trichoderma species are well-studied model fungal organisms used for their biocontrol properties with great potential to alleviate the use of agrochemicals in agriculture. However, identifying and characterizing effective natural products in novel species or strains as biological control products remains a meticulous process with many known challenges to be navigated. Integration of recent advancements in various "omics" technologies, next generation biodesign, machine learning, and artificial intelligence approaches could greatly advance bioprospecting goals. Herein, we propose a roadmap for assessing the potential impact of already known or newly discovered Trichoderma species for biocontrol applications. By screening publicly available Trichoderma genome sequences, we first highlight the prevalence of putative biosynthetic gene clusters and antimicrobial peptides among genomes as an initial step toward predicting which organisms could increase the diversity of natural products. Next, we discuss high-throughput methods for screening organisms to discover and characterize natural products and how these findings impact both fundamental and applied research fields.

Formation, characterization and modeling of emergent synthetic microbial communities.

Microbial communities colonize plant tissues and contribute to host function. How these communities form and how individual members contribute to shaping the microbial community are not well understood. Synthetic microbial communities, where defined individual isolates are combined, can serve as valuable model systems for uncovering the organizational principles of communities. Using genome-defined organisms, systematic analysis by computationally-based network reconstruction can lead to mechanistic insights and the metabolic interactions between species. In this study, 10 bacterial strains isolated from the Populus deltoides rhizosphere were combined and passaged in two different media environments to form stable microbial communities. The membership and relative abundances of the strains stabilized after around 5 growth cycles and resulted in just a few dominant strains that depended on the medium. To unravel the underlying metabolic interactions, flux balance analysis was used to model microbial growth and identify potential metabolic exchanges involved in shaping the microbial communities. These analyses were complemented by growth curves of the individual isolates, pairwise interaction screens, and metaproteomics of the community. A fast growth rate is identified as one factor that can provide an advantage for maintaining presence in the community. Final community selection can also depend on selective antagonistic relationships and metabolic exchanges. Revealing the mechanisms of interaction among plant-associated microorganisms provides insights into strategies for engineering microbial communities that can potentially increase plant growth and disease resistance. Further, deciphering the membership and metabolic potentials of a bacterial community will enable the design of synthetic communities with desired biological functions.

Advances and perspectives in discovery and functional analysis of small secreted proteins in plants.

Small secreted proteins (SSPs) are less than 250 amino acids in length and are actively transported out of cells through conventional protein secretion pathways or unconventional protein secretion pathways. In plants, SSPs have been found to play important roles in various processes, including plant growth and development, plant response to abiotic and biotic stresses, and beneficial plant-microbe interactions. Over the past 10 years, substantial progress has been made in the identification and functional characterization of SSPs in several plant species relevant to agriculture, bioenergy, and horticulture. Yet, there are potentially a lot of SSPs that have not been discovered in plant genomes, which is largely due to limitations of existing computational algorithms. Recent advances in genomics, transcriptomics, and proteomics research, as well as the development of new computational algorithms based on machine learning, provide unprecedented capabilities for genome-wide discovery of novel SSPs in plants. In this review, we summarize known SSPs and their functions in various plant species. Then we provide an update on the computational and experimental approaches that can be used to discover new SSPs. Finally, we discuss strategies for elucidating the biological functions of SSPs in plants.