Metabolic efficiency and amino acid composition in the proteomes of Escherichia coli and Bacillus subtilis

Increase in IAA levels by EPSPS copy number variation relates to fitness advantage in Eleusine indica

BACKGROUND

Long-term use of chemical weed control has led to some weedy species evolving herbicide resistance traits with fitness advantage. Our previous studies revealed glyphosate resistance in an Eleusine indica population due to copy number variation of 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) comes with fitness advantage under non-competitive conditions. Here, transcriptomics and targeted metabolomics were used to investigate physiological basis associated with the fitness advantage.

RESULTS

Relative copy number of EPSPS gene and plant dry weight of the glyphosate-resistant (R) population was 88.3- and 1.2- times, respectively, higher than that in the wild type (WT) plants that were isolated from within the R population. Seven genes were screened to be relevant to fitness growth trait by RNA-seq. The level of aromatic amino acids Tryptophan (Trp), Phenylalanine (Phe) and Tyrosine (Tyr), products in the shikimate pathway catalyzed by EPSPS, was 1.2-times higher in R compared to the WT plants. The metabolites associated with Trp metabolism indole-3-acetic acid (IAA), 3-indolepropionic acid (IPA), indole-3-acetamide (IAM) in the R plants were 2.0-, 1.8- and 1.4- times higher than that in the WT plants, respectively.

CONCLUSION

All the results indicate that fitness advantage in the studied R E. indica population may be caused by higher IAA production due to over-expression of the EPSPS gene and pleiotropically by elevated carbon metabolism. The findings in this research can provide reference information for control strategies to the glyphosate-resistant E. indica. © 2025 Society of Chemical Industry.

Type I-E* CRISPR-Cas of Klebsiella pneumoniae upregulates bacterial virulence by targeting endogenous histidine utilization system

Klebsiella pneumoniae is a globally recognized microbial pathogen with significant clinical impact. The bacterium harbors the clustered regularly interspaced short palindromic repeats (CRISPR)-Cas systems, which provide adaptive immunity against invading foreign nucleic acids. Recent studies suggest that certain CRISPR-Cas systems can regulate endogenous genes, influencing bacterial virulence. However, their role in regulating pathogenicity in K. pneumoniae remains poorly understood. This study investigates the regulatory role of the type I-E* CRISPR-Cas system in a hypervirulent K. pneumoniae strain, focusing on its impact on histidine metabolism and pathogenicity. Transcriptome analyses identified differentially expressed genes (DEGs) between the casABECD-deletion and wild-type strains, including significant upregulation of the histidine utilization (Hut) operon and downregulation of biofilm-related genes. These molecular changes resulted in enhanced histidine metabolic activity, reduced biofilm formation, attenuated virulence in A549 lung epithelial cells, and improved survival of Galleria mellonella, as validated through phenotypic and virulence assays. Our bioinformatic analysis indicated that the CRISPR-Cas system in K. pneumoniae targets the hutT sequence, which is part of the Hut operon. Furthermore, the overexpression of hutT mitigated CRISPR-Cas-mediated repression of the Hut operon, as observed in virulence assays, while simultaneous deletion of hutH and casABECD restored the reduced virulence in the ΔcasABECD strain. Additionally, deletion of casABECD significantly enhances the growth of the strain in medium with histidine as the sole carbon source, highlighting the intricate regulatory role of the CRISPR-Cas system in metabolic adaptation. Collectively, these findings uncover a novel role for the CRISPR-Cas system in regulating metabolic pathways and virulence in hypervirulent K. pneumoniae.IMPORTANCEClustered regularly interspaced short palindromic repeats (CRISPR)-Cas systems are primarily recognized for their roles in adaptive immunity against foreign genetic elements in bacteria. However, emerging evidence indicates that these systems can also regulate endogenous genes, thereby influencing bacterial physiology and virulence. In this study, we demonstrate that the type I-E* CRISPR-Cas system in Klebsiella pneumoniae targets the hutT gene, a critical component of the histidine utilization (Hut) pathway. This targeting potentially impacts hutT transcription and alters the expression of other hut genes, ultimately enhancing bacterial virulence. Our findings reveal a previously unrecognized regulatory mechanism through which CRISPR-Cas systems facilitate metabolic adaptation and pathogenicity in K. pneumoniae. This study broadens our understanding of the multifaceted roles of CRISPR-Cas systems in bacterial physiology and pathobiology, with implications for clinically relevant pathogens.

Complementary Fluorescent Probe Pair Targeting Histidinol Dehydrogenase Provides a Useful Tool for Target Validation

Recent advances in target-based pesticide design have identified numerous novel candidate targets, although their agrochemical potential requires rigorous validation. Fluorescent probes serve as critical tools for tracing molecular interactions and elucidating the target functionality. Herein, we developed a complementary fluorescent probe pair (HDP1 and HDP2) to systematically reveal the challenge of targeting histidinol dehydrogenase (HDH) as an agrochemical target. HDP1 exhibits an outstanding detection limit (0.17 μg/mL), while HDP2 demonstrates excellent imaging capabilities in vivo. HDP1 was used to probe the interactions between inhibitors and substrates with HDH, confirming that HOL, the natural substrate of HDH, exhibits a strong and competitive affinity for HDH similar to that of HDH inhibitors (HDHIs). HDP2 was employed to image HDH in Arabidopsis thaliana, Escherichia coli, and Saccharomyces cerevisiae during treatment with HDHIs or under other stresses to show the change of the flux through the histidine biosynthesis pathway. The results indicate that HDHIs, non-HDH-targeting pesticides, and abiotic stresses can all affect His biosynthesis in plants, bacteria, and fungi. The results also show that various stresses can influence the histidine biosynthesis pathway through the regulation of the pentose phosphate pathway and inhibition of the expression of ATP-phosphoribosyltransferase. It can be concluded that the development of competitive inhibitors for HDH that can compete with HOL and show activity in vivo is a significant challenge. The sensitivity of the His biosynthesis pathway to other stresses complicates the picture and, under different conditions, may provide a positive or negative factor for HDH inhibition by synthetic ligands.

Bioenergetics and the Evolution of Cellular Traits

Evolutionary processes have transformed simple cellular life into a great diversity of forms, ranging from the ubiquitous eukaryotic cell design to the more specific cellular forms of spirochetes, cyanobacteria, ciliates, heliozoans, amoeba, and many others. The cellular traits that constitute these forms require an evolutionary explanation. Ultimately, the persistence of a cellular trait depends on its net contribution to fitness, a quantitative measure. Independent of any positive effects, a cellular trait exhibits a baseline energetic cost that needs to be accounted for when quantitatively examining its net fitness effect. Here, we explore how the energetic burden introduced by a cellular trait quantitatively affects cellular fitness, describe methods for determining cell energy budgets, summarize the costs of cellular traits across the tree of life, and examine how the fitness impacts of these energetic costs compare to other evolutionary forces and trait benefits.

Process Intensification for Recombinant Protein Production in E. coli via Identification of Active Nodes in Cellular Metabolism and Dynamic Flux Balance Analysis

Complex media supplemented with a carbon source are commonly used in bioprocesses for recombinant protein production in Escherichia coli. Optimizing these processes is challenging and requires precise understanding of cellular metabolism and nutrient requirements. Compared to a design of experiments approach that necessitates extensive experimentation, metabolic modeling using a genome scale metabolic model (GEM) offers a more predictive and systematic approach to guide process optimization by identifying specific metabolic bottlenecks. In addition, spent media analysis (SMA) can unravel the preferential utilization of different media components during the bioprocess. Here, we integrated the updated E. coli GEM with time course SMA data from a fed-batch process and performed dynamic flux balance analysis (dFBA) to identify metabolites that function as active nodes and are vital for cellular function. These are potential target supplements to boost cellular activity and in turn the recombinant protein productivity. Using an iterative approach of performing fermentation, SMA, and metabolic modeling, we intensified the bioprocess in just five experimental trials, resulting in a six-fold increase in protein productivity. Our new feeding strategy involved yeast extract with amino acid supplementation (Ser, Thr, Asp, and Glu) and increased oxygen transfer rates. This approach demonstrates significant promise for application in bioprocess intensification.

Disruption-induced changes in syntrophic propionate and acetate oxidation: flocculation, cell proximity, and microbial activity

BACKGROUND

Syntrophic propionate- and acetate-oxidising bacteria (SPOB and SAOB) play a crucial role in biogas production, particularly under high ammonia conditions that are common in anaerobic degradation of protein-rich waste streams. These bacteria rely on close interactions with hydrogenotrophic methanogens to facilitate interspecies electron transfer and maintain thermodynamic feasibility. However, the impact of mixing-induced disruption of these essential syntrophic interactions in biogas systems remains largely unexplored. This study investigates how magnetic stirring and orbital shaking influence degradation dynamics, microbial community composition, and gene expression in syntrophic enrichment communities under high-ammonia conditions.

RESULTS

Stirring significantly delayed the initiation of propionate degradation in one culture and completely inhibited it in the other two parallel cultures, whereas acetate degradation was less affected. Computational fluid dynamics modelling revealed that stirring generated higher shear rates (~ 20 s-1) and uniform cell distribution, while shaking led to lower shear rates and cell accumulation at the bottom of the culture bottle. Visual observations confirmed that stirring inhibited floc formation, while shaking promoted larger flocs compared to the static control condition, which formed smaller flocs and a sheet-like biofilm. Microbial community analysis identified substrate type and degradation progress as primary drivers of community structure, with motion displaying minimal influence. However, metatranscriptomic analysis revealed that motion-induced gene downregulation was associated with motility, surface sensing, and biofilm formation in SAOB and another bacterial species expressing genes for the glycine synthase reductase pathway. Stirring also suppressed oxalate-formate antiporter expression in SPOB, suggesting its dependence on spatial proximity for this energy-conserving mechanism. The strongest gene expression changes of stirring were observed in methanogens, indicating a coupling of the first and last steps of hydrogenotrophic methanogenesis, likely an adaptive strategy for efficient energy conservation. Other downregulated genes included ferrous iron transporters and electron transfer-associated enzymes.

CONCLUSIONS

This study highlights that stirring critically disrupts the initial syntrophic connection between SPOB and methanogens, whereas SAOB communities exhibit greater tolerance to shear stress and disruptive conditions that inhibits aggregate formation. These findings emphasize the importance of carefully managing mixing regimes, especially when attempting to reactivate ammonia-tolerant syntrophic propionate degraders in biogas systems experiencing rapid propionate accumulation under high-ammonia conditions.

Lost in translation: conserved amino acid usage despite extreme codon bias in foraminifera

Analyses of codon usage in eukaryotes suggest that amino acid usage responds to GC pressure so AT-biased substitutions drive higher usage of amino acids with AT-ending codons. Here, we combine single-cell transcriptomics and phylogenomics to explore codon usage patterns in foraminifera, a diverse and ancient clade of predominantly uncultivable microeukaryotes. We curate data from 1,044 gene families in 49 individuals representing 28 genera, generating perhaps the largest existing dataset of data from a predominantly uncultivable clade of protists, to analyze compositional bias and codon usage. We find extreme variation in composition, with a median GC content at fourfold degenerate silent sites below 3% in some species and above 75% in others. The most AT-biased species are distributed among diverse non-monophyletic lineages. Surprisingly, despite the extreme variation in compositional bias, amino acid usage is highly conserved across all foraminifera. By analyzing nucleotide, codon, and amino acid composition within this diverse clade of amoeboid eukaryotes, we expand our knowledge of patterns of genome evolution across the eukaryotic tree of life.IMPORTANCEPatterns of molecular evolution in protein-coding genes reflect trade-offs between substitution biases and selection on both codon and amino acid usage. Most analyses of these factors in microbial eukaryotes focus on model species such as Acanthamoeba, Plasmodium, and yeast, where substitution bias is a primary contributor to patterns of amino acid usage. Foraminifera, an ancient clade of single-celled eukaryotes, present a conundrum, as we find highly conserved amino acid usage underlain by divergent nucleotide composition, including extreme AT-bias at silent sites among multiple non-sister lineages. We speculate that these paradoxical patterns are enabled by the dynamic genome structure of foraminifera, whose life cycles can include genome endoreplication and chromatin extrusion.

Analysis of synonymous codon usage bias in the chloroplast genome of five Caragana

BACKGROUND

The genus Caragana, known for its adaptability and high forage value, is commonly planted to rehabilitate barren land and prevent desertification. Several Caragana species are also used for medicinal purposes. Analysis of synonymous codon usage bias and their primary influencing factors in chloroplast genomes aims to provide insights into molecular research and germplasm innovation for Caragana plants.

RESULTS

The GC content of the five Caragana species ranged from 36.00% to 37.10%, showing a preference for codons ending in A/U, although the codon bias was weak. The screening identified nine to twelve optimal codons, but their frequency of use was low. Correlation analysis, neutrality plots, ENC plots and PR2 plots of the parameters identified two potential groups among the five species: Caragana arborescens and Caragana jubata, and Caragana turkestanica, Caragana opulens and Caragana tibetica. These groups showed a high level of intragroup similarity in the parameter analyses. In the RSCU cluster tree analysis, Caragana turkestanica and Caragana arborescens grouped together, while Caragana tibetica, Caragana jubata and Caragana opulens formed a separate clade in the CDS sequence and complete sequence phylogenetic tree analysis.

CONCLUSIONS

The codon usage bias in the chloroplast genomes of the five Caragana species showed high similarity, suggesting that natural selection has a greater influence on codon bias than mutation. Furthermore, the identified optimal codons provide valuable insights for germplasm improvement of Caragana plants.

Bacterial Amino Acid Auxotrophies Enable Energetically Costlier Proteomes

The outsourcing of amino acid (AA) production to the environment is relatively common across the tree of life. We recently showed that the massive loss of AA synthesis capabilities in animals is governed by selective pressure linked to the energy costs of AA production. Paradoxically, these AA auxotrophies facilitated the evolution of costlier proteomes in animals by enabling the increased use of energetically expensive AAs. Experiments in bacteria have shown that AA auxotrophies can provide a fitness advantage in competition with prototrophic strains. However, it remains unclear whether energy-related selection also drives the evolution of bacterial AA auxotrophies and whether this affects the usage of expensive AAs in bacterial proteomes. To investigate these questions, we computationally determined AA auxotrophy odds across 980 bacterial genomes representing diverse taxa and calculated the energy costs of all their proteins. Here, we show that auxotrophic AAs are generally more expensive to synthesize than prototrophic AAs in bacteria. Moreover, we found that the cost of auxotrophic AAs significantly correlates with the cost of their respective proteomes. Interestingly, out of all considered taxa, Mollicutes and Borreliaceae-chronic pathogens highly successful in immune evasion-have the most AA auxotrophies and code for the most expensive proteomes. These findings indicate that AA auxotrophies in bacteria, similar to those in animals, are shaped by selective pressures related to energy management. Our study reveals that bacterial AA auxotrophies act as costly outsourced functions, enabling bacteria to explore protein sequence space more freely. It remains to be investigated whether this relaxed use of expensive AAs also enabled auxotrophic bacteria to evolve proteins with improved or novel functionality.

Post-transcriptional regulation of aromatic amino acid metabolism by GcvB small RNA in Escherichia coli

Escherichia coli synthesizes aromatic amino acids (AAAs) through the common pathway to produce the precursor, chorismate, and the three terminal pathways to convert chorismate into Phe, Tyr, and Trp. E. coli also imports exogenous AAAs through five transporters. GcvB small RNA post-transcriptionally regulates more than 50 genes involved in amino acid uptake and biosynthesis in E. coli, but the full extent of GcvB regulon is still underestimated. This study examined all genes involved in AAA biosynthesis and transport using translation reporter assay and qRT-PCR analysis. In addition to previously verified targets, aroC, aroP, and trpE, we identified new target genes that were significantly repressed by GcvB primarily via the R1 seed region. Exceptionally, GcvB strongly inhibits the expression of aroG, which encodes the major isozyme of the first reaction in the common pathway, through direct base pairing between the aroG translation initiation region and the GcvB R3 seed sequence. RNase E mediates the degradation of target mRNAs except aroC and aroP via its C-terminal domain. GcvB overexpression prolongs the lag phase and reduces the growth rate in minimal media supplemented with AAAs and confers resistance to an antibiotic compound, azaserine, by repressing AAA transporters.IMPORTANCEE. coli strains have been genetically modified in relevant transcription factors and biosynthetic enzymes for industrial use in the fermentative production of aromatic amino acids (AAAs) and their derivative compounds. This study focuses on GcvB small RNA, a global regulator of amino acid metabolism in E. coli, and identifies new GcvB targets involved in AAA biosynthesis and uptake. GcvB represses the expression of the first and last enzymes of the common pathway and the first enzymes of Trp and Phe terminal pathways. GcvB also limits import of AAAs. This paper documents the impact of RNA-mediated regulation on AAA metabolism in E. coli.

Does metabolic rate influence genome-wide amino acid composition in the course of animal evolution?

Natural selection is believed to shape amino acid usage of the proteome by minimizing the energy cost of protein biosynthesis. Although this hypothesis explains well the amino acid frequency (AAfrequency) difference among the 20 common amino acids within a given genome (species), whether it is applicable to cross-species difference remains to be inspected. Here, we proposed and tested a "metabolic rate hypothesis," which suggests that metabolic rate impacts genome-wide AAfrequency, considering that the energy allocated to protein biosynthesis is under selection pressure due to metabolic rate constraint. We performed integrated phylogenetic comparative analyses on proteomic sequence and metabolic rate data of 166 species covering 130 eumetazoan orders. We showed that resting metabolic rate (RMR) was significantly linked to AAfrequency variation across animal lineages, with a contribution comparable to or greater than genomic traits such as GC content and codon usage bias. Consistent with the metabolic rate hypothesis, low-energy-cost amino acids are observed to be more likely at higher frequency in animal species with high (residual) metabolic rate. Correlated evolution of RMR and AAfrequency was further inferred being driven by adaptation. The relationship between RMR and AAfrequency varied greatly among amino acids, most likely reflecting a trade-off among various interacting factors. Overall, there exists no "one-size-fits-all" predictor for AAfrequency, and integrated investigation of multilevel traits is indispensable for a fuller understanding of AAfrequency variation and evolution in animal.

Codon bias, nucleotide selection, and genome size predict in situ bacterial growth rate and transcription in rewetted soil

In soils, the first rain after a prolonged dry period represents a major pulse event impacting soil microbial community function, yet we lack a full understanding of the genomic traits associated with the microbial response to rewetting. Genomic traits such as codon usage bias and genome size have been linked to bacterial growth in soils-however, often through measurements in culture. Here, we used metagenome-assembled genomes (MAGs) with 18O-water stable isotope probing and metatranscriptomics to track genomic traits associated with growth and transcription of soil microorganisms over one week following rewetting of a grassland soil. We found that codon bias in ribosomal protein genes was the strongest predictor of growth rate. We also found higher growth rates in bacteria with smaller genomes, suggesting that reduced genome size enables a faster response to pulses in soil bacteria. Faster transcriptional upregulation of ribosomal protein genes was associated with high codon bias and increased nucleotide skew. We found that several of these relationships existed within phyla, indicating that these associations between genomic traits and activity could be generalized characteristics of soil bacteria. Finally, we used publicly available metagenomes to assess the distribution of codon bias across a pH gradient and found that microbial communities in higher pH soils-which are often more water limited and pulse driven-have higher codon usage bias in their ribosomal protein genes. Together, these results provide evidence that genomic characteristics affect soil microbial activity during rewetting and pose a potential fitness advantage for soil bacteria where water and nutrient availability are episodic.

Impact of trace metal supplementation on anaerobic biological methanation under hydrogen and carbon dioxide starvation

Biomethanation is a crucial process occurring in natural and engineered systems which can reduce carbon dioxide to methane impacting the global carbon cycle. However, little is known about the effect of on-and-off gaseous provision and micronutrients on bioconversion. Here, anaerobic microbiomes underwent intermittent feeding with incremental starvations and selective metal supplementation to assess the impact of hydrogen and carbon dioxide availability on microbial physiology. Resilience was tested under differential cultivations in basal medium supplemented with either nickel or cobalt. Nickel-augmented cultures exhibited faster recovery upon starvation, suggesting a beneficial effect. Dominant Methanothermobacter thermautotrophicus demonstrated robust growth, genetic stability and transcriptional downregulation when starved. Conversely, bacteria were plastic and prone to genetic fluctuations, accumulating mutations on genes encoding for ABC-transporters and C-metabolism enzymes. This study pioneers cellular resilience and response to micronutrient supplementation in anaerobic carbon dioxide-fixating microbiomes, offering valuable insights into microbial activity recovery after carbon and electron donor deprivation.

Amino acid sequence encodes protein abundance shaped by protein stability at reduced synthesis cost

Understanding what drives protein abundance is essential to biology, medicine, and biotechnology. Driven by evolutionary selection, an amino acid sequence is tailored to meet the required abundance of a proteome, underscoring the intricate relationship between sequence and functional demand. Yet, the specific role of amino acid sequences in determining proteome abundance remains elusive. Here we show that the amino acid sequence alone encodes over half of protein abundance variation across all domains of life, ranging from bacteria to mouse and human. With an attempt to go beyond predictions, we trained a manageable-size Transformer model to interpret latent factors predictive of protein abundances. Intuitively, the model's attention focused on the protein's structural features linked to stability and metabolic costs related to protein synthesis. To probe these relationships, we introduce MGEM (Mutation Guided by an Embedded Manifold), a methodology for guiding protein abundance through sequence modifications. We find that mutations which increase predicted abundance have significantly altered protein polarity and hydrophobicity, underscoring a connection between protein structural features and abundance. Through molecular dynamics simulations we revealed that abundance-enhancing mutations possibly contribute to protein thermostability by increasing rigidity, which occurs at a lower synthesis cost.

Disentangling protein metabolic costs in human cells and tissues

While more data are becoming available on gene activity at different levels of biological organization, our understanding of the underlying biology remains incomplete. Here, we introduce a metabolic efficiency framework that considers highly expressed proteins (HEPs), their length, and biosynthetic costs in terms of the amino acids (AAs) they contain to address the observed balance of expression costs in cells, tissues, and cancer transformation. Notably, the combined set of HEPs in either cells or tissues shows an abundance of large and costly proteins, yet tissues compensate this with short HEPs comprised of economical AAs, indicating a stronger tendency toward mitigating costs. We additionally observe that short proteins are prevalent HEPs across individual cells and tissues, whereas long ones are more specific. Furthermore, the precise proportion of short, long, economical, or costly HEP classes indicates that particular cell types and tissues align more closely with the metabolic efficiency model, with some tissues displaying behavior akin to their constituent cells. Finally, tumors typically increase the production of short and low-cost HEPs compared with matched normal tissues, while genes that decrease their high expression levels in tumors often tend to be associated with high costs. Overall, the metabolic efficiency framework serves as a useful simplifying model for interpreting genome-wide expression data across scales.

Integrating Experimental and Computational Analyses of Yeast Protein Profiles for Optimizing the Production of High-Quality Microbial Proteins

Microbial proteins represent a promising solution to address the escalating global demand for protein, particularly in regions with limited arable land. Yeasts, such as Saccharomyces cerevisiae, are robust and safe protein-producing strains. However, the utilization of non-conventional yeast strains for microbial protein production has been hindered, partly due to a lack of comprehensive understanding of protein production traits. In this study, we conducted experimental analyses focusing on the growth, protein content, and amino acid composition of nine yeast strains, including one S. cerevisiae strain, three Yarrowia lipolytica strains, and five Pichia spp. strains. We identified that, though Y. lipolytica and Pichia spp. strains consumed glucose at a slower rate compared to S. cerevisiae, Pichia spp. strains showed a higher cellular protein content, and Y. lipolytica strains showed a higher glucose-to-biomass/protein yield and methionine content. We further applied computational approaches to explain that metabolism economy was the main underlying factor for the limited amount of scarce/carbon-inefficient amino acids (such as methionine) within yeast cell proteins. We additionally verified that the specialized metabolism was a key reason for the high methionine content in Y. lipolytica strains, and proposed Y. lipolytica strain as a potential producer of high-quality single-cell protein rich in scarce amino acids. Through experimental evaluation, we identified Pichia jadinii CICC 1258 as a potential strain for high-quality protein production under unfavorable pH/temperature conditions. Our work suggests a promising avenue for optimizing microbial protein production, identifying the factors influencing amino acid composition, and paving the way for the use of unconventional yeast strains to meet the growing protein demands.

Effect of Light Regime on Candidatus Puniceispirillum marinum IMCC1322 in Nutrient-Replete Conditions

Previous studies showed no improvement in bacterial biomass for Candidatus Puniceispirillum marinum IMCC1322 under light regimes. Nevertheless, in nutrient-replete cultures with higher inoculating cell densities, strain IMCC1322 exhibited proteorhodopsin photoheterotrophy. Increasing both inoculum size and the amino acid pool can eliminate quorum sensing and starvation responses in strain IMCC1322. Light regimes affected IMCC1322 cultures in stationary/death phases, where cellular ATP levels ranged from 0.0331 to 1.74 mM, with ATP/cell ranging from 13.9 to 367 zeptomoles. In nutrient-depleted conditions, strain IMCC1322 may suffer from excessive protons generated by proteorhodopsin under light conditions. IMCC1322 may tolerate excessive periplasmic protons through ATP-dependent proton pumping and protonation of augmented amino acids. Meanwhile, acid stress could also be mitigated by refining membrane permeability through unsaturation and cyclopropanation of phospholipids. Oceanic bacteria such as IMCC1322 and SAR11 preferred anaplerotic TCA cycles over glycolysis and rely on the Entner-Doudoroff (ED) pathway for growth. Although ATP generation is less efficient in the ED pathway, it offers advantages during rapid growth owing to its strong thermodynamic driving force. The metabolism of IMCC1322 favors gluconeogenesis over glycolysis, aligning with the metabolism of SAR11 reported in previous studies. However, the additional light-driven, PR-dependent ATP synthesis in IMCC1322 is expected to be insufficient to support protein turnover after the log phase, as well as in nutrient-limited conditions. Stable isotope measurements showed no significant differences in the inorganic carbon assimilation between constant light and constant dark cultures in late log phase.

Expanded genome and proteome reallocation in a novel, robust Bacillus coagulans strain capable of utilizing pentose and hexose sugars

Bacillus coagulans, a Gram-positive thermophilic bacterium, is recognized for its probiotic properties and recent development as a microbial cell factory. Despite its importance for biotechnological applications, the current understanding of B. coagulans' robustness is limited, especially for undomesticated strains. To fill this knowledge gap, we characterized the metabolic capability and performed functional genomics and systems analysis of a novel, robust strain, B. coagulans B-768. Genome sequencing revealed that B-768 has the largest B. coagulans genome known to date (3.94 Mbp), about 0.63 Mbp larger than the average genome of sequenced B. coagulans strains, with expanded carbohydrate metabolism and mobilome. Functional genomics identified a well-equipped genetic portfolio for utilizing a wide range of C5 (xylose, arabinose), C6 (glucose, mannose, galactose), and C12 (cellobiose) sugars present in biomass hydrolysates, which was validated experimentally. For growth on individual xylose and glucose, the dominant sugars in biomass hydrolysates, B-768 exhibited distinct phenotypes and proteome profiles. Faster growth and glucose uptake rates resulted in lactate overflow metabolism, which makes B. coagulans a lactate overproducer; however, slower growth and xylose uptake diminished overflow metabolism due to the high energy demand for sugar assimilation. Carbohydrate Transport and Metabolism (COG-G), Translation (COG-J), and Energy Conversion and Production (COG-C) made up 60%-65% of the measured proteomes but were allocated differently when growing on xylose and glucose. The trade-off in proteome reallocation, with high investment in COG-C over COG-G, explains the xylose growth phenotype with significant upregulation of xylose metabolism, pyruvate metabolism, and tricarboxylic acid (TCA) cycle. Strain B-768 tolerates and effectively utilizes inhibitory biomass hydrolysates containing mixed sugars and exhibits hierarchical sugar utilization with glucose as the preferential substrate.IMPORTANCEThe robustness of B. coagulans makes it a valuable microorganism for biotechnology applications; yet, this phenotype is not well understood at the cellular level. Through phenotypic characterization and systems analysis, this study elucidates the functional genomics and robustness of a novel, undomesticated strain, B. coagulans B-768, capable of utilizing inhibitory switchgrass biomass hydrolysates. The genome of B-768, enriched with carbohydrate metabolism genes, demonstrates high regulatory capacity. The coordination of proteome reallocation in Carbohydrate Transport and Metabolism (COG-G), Translation (COG-J), and Energy Conversion and Production (COG-C) is critical for effective cell growth, sugar utilization, and lactate production via overflow metabolism. Overall, B-768 is a novel, robust, and promising B. coagulans strain that can be harnessed as a microbial biomanufacturing platform to produce chemicals and fuels from biomass hydrolysates.

tRNA regulation and amino acid usage bias reflect a coordinated metabolic adaptation in Plasmodium falciparum

An adaptive feature of malaria-causing parasites is the digestion of host hemoglobin (HB) to acquire amino acids (AAs). Here, we describe a link between nutrient availability and translation dependent regulation of gene expression as an adaptive strategy. We show that tRNA expression in Plasmodium falciparum does not match the decoding need expected for optimal translation. A subset of tRNAs decoding AAs that are insufficiently provided by HB are lowly expressed, wherein the abundance of a protein-coding transcript is negatively correlated with the decoding requirement of these tRNAs. Proliferation-related genes have evolved a high requirement of these tRNAs, thereby proliferation can be modulated by repressing protein synthesis of these genes during nutrient stress. We conclude that the parasite modulates translation elongation by maintaining a discordant tRNA profile to exploit variations in AA-composition among genes as an adaptation strategy. This study exemplifies metabolic adaptation as an important driving force for protein evolution.

Unveiling tryptophan dynamics and functions across model organisms via quantitative imaging

BACKGROUND

Tryptophan is an essential amino acid involved in critical cellular processes in vertebrates, serving as a precursor for serotonin and kynurenine, which are key neuromodulators to influence neural and immune functions. Systematic and quantitative measurement of tryptophan is vital to understanding these processes.

RESULTS

Here, we utilized a robust and highly responsive green ratiometric indicator for tryptophan (GRIT) to quantitatively measure tryptophan dynamics in bacteria, mitochondria of mammalian cell cultures, human serum, and intact zebrafish. At the cellular scale, these quantitative analyses uncovered differences in tryptophan dynamics across cell types and organelles. At the whole-organism scale, we revealed that inflammation-induced tryptophan concentration increases in zebrafish brain led to elevated serotonin and kynurenine levels, prolonged sleep duration, suggesting a novel metabolic connection between immune response and behavior. Moreover, GRIT's application in detecting reduced serum tryptophan levels in patients with inflammation symptoms suggests its potential as a high-throughput diagnostic tool.

CONCLUSIONS

In summary, this study introduces GRIT as a powerful method for studying tryptophan metabolism and its broader physiological implications, paving the way for new insights into the metabolic regulation of health and disease across multiple biological scales.

Waste Nitrogen Upcycling to Amino Acids during Anaerobic Fermentation on Biochar: An Active Strategy for Regulating Metabolic Reducing Power

This study proposes a novel strategy that utilizes biochar (BC) during anaerobic fermentation (AF) to generate amino acids (AAs) toward nitrogen upcycling. The BC, pyrolyzed at 800 °C (BC800) to enhance graphite structures and electron-accepting sites, effectively addresses issues related to biosynthetic reducing power nicotinamide adenine dinucleotide phosphate insufficiency by altering cellular conditions and alleviates feedback inhibition through the immobilization of end products. This process establishes unique microbial signaling and energy networks, with Escherichia coli becoming dominant in the biofilm. The conversion rate of ammonia-N to AAs-N within the biofilm reached 67.4% in BC800-AF, which was significantly higher compared to the levels in other AF reactors with BC pyrolyzed at 600 and 400 °C (45.9 and 22.5%, respectively), as well as a control AF reactor (<5%). Furthermore, in BC800-AF, the aromatic AAs (Aro-AAs) were as high as 70.8% of the AAs within the biofilm. The activities of key enzymes for Aro-AAs biosynthesis uniquely positively correlated with the electron-accepting capacity on BC800 (R2 ≥ 0.95). These findings hold promise for transforming existing AF reactors into factories that produce BC-based AAs, providing a more sustainable fertilizing agent than chemical fertilizers.

Non-senescent species are not immortal: Stress and decline in two planaria species

Potential immortality is observed in several species (e.g. prickly pear cactus, hydra and flatworms) and is indicative of their negligible or even negative senescence rates. Unlike in senescent species, which experience reduced individual performance with age due to physiological degradation, species with negligible or negative senescence display mortality rates that remain constant or decline with age, respectively. These rates vary across taxa and are correlated with life history traits. Yet, the extent to which variable resource availability, a key driver of variation in life history traits, impacts species that show negligible or negative senescence is currently unknown. Here, we examine whether and how variation in the quantity, quality and feeding interval of resources impact population structure, population performance and life history trait trade-offs in two long-lived planaria that do not senesce: Schmidtea mediterranea and Dugesia tahitiensis. In a full factorial design, different combinations of resource quantity (reduced intake, standard intake and high intake) and quality (high and low quality) were provided in two different feeding intervals (7-day and 14-day intervals) for 19 weeks. We show that variability in resource availability, via decreases in quantity, quality and frequency of resources, does not diminish population viability in either species but does result in suboptimal conditions of stress in S. mediterranea. The high population viability we report can be attributed to two different mechanisms: increased reproduction or increased investment into maintenance at the expense of reproduction. Moreover, which mechanism was responsible for said high population viability was context-dependent and modulated by the specific life history strategy of the two planaria species. We show that suboptimal conditions can cause stress responses that have significant impacts on non-senescent species. The context-dependent response we observe suggests that species that do not senesce but are subject to suboptimal conditions of stress may ultimately exhibit declines in performance and ultimately die. A clearer understanding of the impact of suboptimal conditions of resource availability on non-senescent species is needed to determine the extent of stress experienced and ultimately whether a species can truly be immortal.

Differential amino acid usage leads to ubiquitous edge effect in proteomes across domains of life that can be explained by amino acid secondary structure propensities

Amino acids are the building blocks of proteins and enzymes which are essential for life. Understanding amino acid usage offers insights into protein function and molecular mechanisms underlying life histories. However, genome-wide patterns of amino acid usage across domains of life remain poorly understood. Here, we analysed the proteomes of 5590 species across four domains and found that only a few amino acids are consistently the most and least used. This differential usage results in lower amino acid usage diversity at the most and least frequent ranks, creating a ubiquitous inverted U-shape pattern of amino acid diversity and rank which we call an 'edge effect' across proteomes and domains of life. This effect likely stems from protein secondary structural constraints, not the evolutionary chronology of amino acid incorporation into the genetic code, highlighting the functional rather than evolutionary influences on amino acid usage. We also tested other contemporary hypotheses regarding amino acid usage in proteomes and found that amino acid usage varies across life's domains and is only weakly influenced by growth temperature. Our findings reveal a novel and pervasive amino acid usage pattern across genomes with the potential to help us probe deep evolutionary relationships and advance synthetic biology.

Bacterial amino acid chemotaxis: a widespread strategy with multiple physiological and ecological roles

Chemotaxis is the directed, flagellum-based movement of bacteria in chemoeffector gradients. Bacteria respond chemotactically to a wide range of chemoeffectors, including amino, organic, and fatty acids, sugars, polyamines, quaternary amines, purines, pyrimidines, aromatic hydrocarbons, oxygen, inorganic ions, or polysaccharides. Most frequent are chemotactic responses to amino acids (AAs), which were observed in numerous bacteria regardless of their phylogeny and lifestyle. Mostly chemoattraction responses are observed, although a number of bacteria are repelled from certain AAs. Chemoattraction is associated with the important metabolic value of AAs as growth substrates or building blocks of proteins. However, additional studies revealed that AAs are also sensed as environmental cues. Many chemoreceptors are specific for AAs, and signaling is typically initiated by direct ligand binding to their four-helix bundle or dCache ligand-binding domains. Frequently, bacteria possess multiple AA-responsive chemoreceptors that at times possess complementary AA ligand spectra. The identification of sequence motifs in the binding sites at dCache_1 domains has permitted to define an AA-specific family of dCache_1AA chemoreceptors. In addition, AAs are among the ligands recognized by broad ligand range chemoreceptors, and evidence was obtained for chemoreceptor activation by the binding of AA-loaded solute-binding proteins. The biological significance of AA chemotaxis is very ample including in biofilm formation, root and seed colonization by beneficial bacteria, plant entry of phytopathogens, colonization of the intestine, or different virulence-related features in human/animal pathogens. This review provides insights that may be helpful for the study of AA chemotaxis in other uncharacterized bacteria.

Microbial coadaptation drives the dynamic stability of microecology in mainstream and sidestream anammox systems under exposure of progesterone

Microbial cooperation determines the efficacy of wastewater biological treatment, and the adaptability of microorganisms to environmental stresses varies. Recently, extensive use of hormones results in their inevitable discharge into aquatic environment. Therefore, mainstream and sidestream anammox reactors were constructed in this study to evaluate their removal performance of progesterone and nitrogen simultaneously, the adaptability of anammox consortia to progesterone stress and the corresponding regulation mechanism. Both anammox processes had the resilience to progesterone stress, with the average nitrogen removal efficiency exceeding 90 %. At the same time, progesterone removal efficiency also exceeded 70 %. In contrast, microbial community in the mainstream reactors was more susceptible to progesterone interference. The adaptation of anammox consortia mainly depended on microbial cooperation and molecular regulation. Initially, bacteria secreted more extracellular polymeric substances to detain progesterone. Biodegradation also contributed to mitigating the side effect of progesterone, which was demonstrated by the proliferation of potential degrading bacteria such as Bacillus salacetis, Bacillus wiedmannii and Rhodococcus erythropolis. In addition, the enhancement of microbial interaction intensity drove their cooperation to enhance adaptability and maintain stable performance. Combined with metagenomic and metatranscriptomic analyses, such microbial adaptability was enhanced through molecular regulations, including the energy redistribution for amino acid synthesis and alteration of key metabolic pathways. Related functional gene expressions and microbial interactions were, in turn, regulated by quorum sensing. This work verifies the feasibility of anammox process in hormone-containing wastewater treatment and provides a holistic understanding of molecular mechanism of microbial interaction and coadaptation to stress.

The amino acid composition of a protein influences its expression

The quantity of each protein in a cell only is only partially correlated with its gene transcription rate. Independent influences on protein synthesis levels include mRNA sequence motifs, amino acyl-tRNA synthesis levels, elongation factor action, and protein susceptibility to degradation. Here we report that the amino acid composition of a protein can also influence its expression level in two distinct ways. The nutritional classification of amino acids in animals reflects their potential for scarcity-essential amino acids (EAA) are reliant on dietary supply, non-essential amino acids (NEAA) from internal biosynthesis, and conditionally essential amino acids (CEAA) from both. Accessing public proteomic datasets, we demonstrate that a protein's CEAA sequence composition is inversely correlated with expression-a correlation enhanced during rapid cellular proliferation-suggesting CEAA availability can limit translation. Similarly, proteins with the most extreme compositions of EAA are generally reduced in abundance. These latter proteins participate in biological systems such as taste and food-seeking behaviour, oxidative phosphorylation, and chemokine function, and so linking their expression to EAA availability may act as a homeostatic response to malnutrition. Protein composition can also influence general human phenotypes and disease susceptibility: stature proteins are enriched in CEAAs, and a curated dataset of over 700 cancer proteins is significantly under-represented in EAAs. We also show that individual amino acids can influence protein expression across all kingdoms of life and that this effect appears to be rooted in the unchanging structural and mRNA encoding features of each amino acid. Species-specific environmental survival pathways are shown to be enriched in proteins with individual amino acid compositions favouring higher expression. These two forms of amino acid-driven protein expression regulation promise new insights into systems biology, evolutionary studies, experimental research design, and public health intervention.

Cellular location shapes quaternary structure of enzymes

The main forces driving protein complex evolution are currently not well understood, especially in homomers, where quaternary structure might frequently evolve neutrally. Here we examine the factors determining oligomerisation by analysing the evolution of enzymes in circumstances where homomers rarely evolve. We show that 1) In extracellular environments, most enzymes with known structure are monomers, while in the cytoplasm homomers, indicating that the evolution of oligomers is cellular environment dependent; 2) The evolution of quaternary structure within protein orthogroups is more consistent with the predictions of constructive neutral evolution than an adaptive process: quaternary structure is gained easier than it is lost, and most extracellular monomers evolved from proteins that were monomers also in their ancestral state, without the loss of interfaces. Our results indicate that oligomerisation is context-dependent, and even when adaptive, in many cases it is probably not driven by the intrinsic properties of enzymes, like their biochemical function, but rather the properties of the environment where the enzyme is active. These factors might be macromolecular crowding and excluded volume effects facilitating the evolution of interfaces, and the maintenance of cellular homeostasis through shaping cytoplasm fluidity, protein degradation, or diffusion rates.

Comparing the complexity of written and molecular symbolic systems

Symbolic systems (SSs) are uniquely products of living systems, such that symbolism and life may be inextricably intertwined phenomena. Within a given SS, there is a range of symbol complexity over which signaling is functionally optimized. This range exists relative to a complex and potentially infinitely large background of latent, unused symbol space. Understanding how symbol sets sample this latent space is relevant to diverse fields including biochemistry and linguistics. We quantitatively explored the graphic complexity of two biosemiotic systems: genetically encoded amino acids (GEAAs) and written language. Molecular and graphical notions of complexity are highly correlated for GEAAs and written language. Symbol sets are generally neither minimally nor maximally complex relative to their latent spaces, but exist across an objectively definable distribution, with the GEAAs having especially low complexity. The selection pressures guiding these disparate systems are explicable by symbol production and disambiguation efficiency. These selection pressures may be universal, offer a quantifiable metric for comparison, and suggest that all life in the Universe may discover optimal symbol set complexity distributions with respect to their latent spaces. If so, the "complexity" of individual components of SSs may not be as strong a biomarker as symbol set complexity distribution.

The C. elegans Myc-family of transcription factors coordinate a dynamic adaptive response to dietary restriction

Dietary restriction (DR), the process of decreasing overall food consumption over an extended period of time, has been shown to increase longevity across evolutionarily diverse species and delay the onset of age-associated diseases in humans. In Caenorhabditis elegans, the Myc-family transcription factors (TFs) MXL-2 (Mlx) and MML-1 (MondoA/ChREBP), which function as obligate heterodimers, and PHA-4 (orthologous to FOXA) are both necessary for the full physiological benefits of DR. However, the adaptive transcriptional response to DR and the role of MML-1::MXL-2 and PHA-4 remains elusive. We identified the transcriptional signature of C. elegans DR, using the eat-2 genetic model, and demonstrate broad changes in metabolic gene expression in eat-2 DR animals, which requires both mxl-2 and pha-4. While the requirement for these factors in DR gene expression overlaps, we found many of the DR genes exhibit an opposing change in relative gene expression in eat-2;mxl-2 animals compared to wild-type, which was not observed in eat-2 animals with pha-4 loss. Surprisingly, we discovered more than 2000 genes synthetically dysregulated in eat-2;mxl-2, out of which the promoters of down-regulated genes were substantially enriched for PQM-1 and ELT-1/3 GATA TF binding motifs. We further show functional deficiencies of the mxl-2 loss in DR outside of lifespan, as eat-2;mxl-2 animals exhibit substantially smaller brood sizes and lay a proportion of dead eggs, indicating that MML-1::MXL-2 has a role in maintaining the balance between resource allocation to the soma and to reproduction under conditions of chronic food scarcity. While eat-2 animals do not show a significantly different metabolic rate compared to wild-type, we also find that loss of mxl-2 in DR does not affect the rate of oxygen consumption in young animals. The gene expression signature of eat-2 mutant animals is consistent with optimization of energy utilization and resource allocation, rather than induction of canonical gene expression changes associated with acute metabolic stress, such as induction of autophagy after TORC1 inhibition. Consistently, eat-2 animals are not substantially resistant to stress, providing further support to the idea that chronic DR may benefit healthspan and lifespan through efficient use of limited resources rather than broad upregulation of stress responses, and also indicates that MML-1::MXL-2 and PHA-4 may have distinct roles in promotion of benefits in response to different pro-longevity stimuli.

Cross-biome microbial networks reveal functional redundancy and suggest genome reduction through functional complementarity

The structure of microbial communities arises from a multitude of factors, including the interactions of microorganisms with each other and with the environment. In this work, we sought to disentangle those drivers by performing a cross-study, cross-biome meta-analysis of microbial occurrence data in more than 5000 samples, applying a novel network clustering algorithm aimed to capture conditional taxa co-occurrences. We then examined the phylogenetic and functional composition of the resulting clusters, and searched for global patterns of assembly both at the community level and in the presence/absence of individual metabolic pathways.Our analysis highlighted the prevalence of functional redundancy in microbial communities, particularly between taxa that co-occur in more than one environment, pointing to a relationship between functional redundancy and environmental adaptation. In spite of this, certain pathways were observed in fewer taxa than expected by chance, suggesting the presence of auxotrophy, and presumably cooperation among community members. This hypothetical cooperation may play a role in genome reduction, since we observed a negative relationship between the size of bacterial genomes and the size of the community they belong to.Overall, our results suggest the microbial community assembly is driven by universal principles that operate consistently across different biomes and taxonomic groups.

Mechanisms of anammox granular sludge reactor effluent as biostimulant: Shaping microenvironment for anammox metabolism

Effluent from anammox granular sludge (AnGS) bioreactor contains microbes and microbial products. This study explored mechanisms of utilizing AnGS-effluent as biostimulant for anammox process enhancement. Compared with no AnGS-effluent supplemented control reactor, 5.0 and 1.3 times higher ammonium nitrogen and total inorganic nitrogen removal rates, respectively were obtained with continuous AnGS-effluent supplementation after 98 days' operation. Anammox bacteria from Candidatus Brocadia accounted for 0.1 % (DNA level) and 1.3 %-1.5 % (RNA level) in control reactor, and 2.9 % (DNA level) and 54.5 %-55.4 % (RNA level) in the AnGS-effluent-fed reactor. Influent microbial immigration evaluation showed that bacterial immigration via AnGS-effluent supplementation was not the main contributor to active anammox community development. Amino acids biosynthesis, B-vitamins and coenzymes metabolism related pathways were facilitated by AnGS-effluent supplementation. AnGS-effluent supplementation aided anammox metabolic activity by shaping microenvironment and microbial interactions. This study provides insights into enhancing anammox bacterial metabolism with AnGS-effluent microbial products as biostimulant.

Large-scale investigation of species-specific orphan genes in the human gut microbiome elucidates their evolutionary origins

Species-specific genes, also known as orphans, are ubiquitous across life's domains. In prokaryotes, species-specific orphan genes (SSOGs) are mostly thought to originate in external elements such as viruses followed by horizontal gene transfer, whereas the scenario of native origination, through rapid divergence or de novo, is mostly dismissed. However, quantitative evidence supporting either scenario is lacking. Here, we systematically analyzed genomes from 4644 human gut microbiome species and identified more than 600,000 unique SSOGs, representing an average of 2.6% of a given species' pangenome. These sequences are mostly rare within each species yet show signs of purifying selection. Overall, SSOGs use optimal codons less frequently, and their proteins are more disordered than those of conserved genes (i.e., non-SSOGs). Importantly, across species, the GC content of SSOGs closely matches that of conserved ones. In contrast, the ∼5% of SSOGs that share similarity to known viral sequences have distinct characteristics, including lower GC content. Thus, SSOGs with similarity to viruses differ from the remaining SSOGs, contrasting an external origination scenario for most of them. By examining the orthologous genomic region in closely related species, we show that a small subset of SSOGs likely evolved natively de novo and find that these genes also differ in their properties from the remaining SSOGs. Our results challenge the notion that external elements are the dominant source of prokaryotic genetic novelty and will enable future studies into the biological role and relevance of species-specific genes in the human gut.

Quantitative proteomics insights into Chlamydomonas reinhardtii thermal tolerance enhancement by a mutualistic interaction with Sinorhizobium meliloti

Interactions between photosynthetic microalgae and bacteria impact the physiology of both partners, which influence the fitness and ecological trajectories of each partner in an environmental context-dependent manner. Thermal tolerance of Chlamydomonas reinhardtii can be enhanced through a mutualistic interaction with vitamin B12 (cobalamin)-producing Sinorhizobium meliloti. Here, we used label-free quantitative proteomics to reveal the metabolic networks altered by the interaction under normal and high temperatures. We created a scenario where the growth of Sinorhizobium requires carbon provided by Chlamydomonas for growth in co-cultures, and survival of Chlamydomonas under high temperatures relies on cobalamin and possibly other metabolites produced by Sinorhizobium. Differential abundance analysis identified proteins produced by each partner in co-cultures compared to mono-cultures at each temperature. Proteins involved in cobalamin production by Sinorhizobium increased in the presence of Chlamydomonas under elevated temperatures, whereas in Chlamydomonas, there was an increase in cobalamin-dependent methionine synthase and certain proteins associated with methylation reactions. Co-cultivation and heat stress strongly modulated the central metabolism of both partners as well as various transporters that could facilitate nutrient cross-utilization. Co-cultivation modulated expression of various components of two- or one-component signal transduction systems, transcriptional activators/regulators, or sigma factors, suggesting complex regulatory networks modulate the interaction in a temperature-dependent manner. Notably, heat and general stress-response and antioxidant proteins were upregulated in co-cultures, suggesting that the interaction is inherently stressful to each partner despite the benefits of mutualism. Our results shed insight into the metabolic tradeoffs required for mutualism and how metabolic networks are modulated by elevated temperature.

IMPORTANCE

Photosynthetic microalgae are key primary producers in aquatic ecosystems, playing an important role in the global carbon cycle. Nearly every alga lives in association with a diverse community of microorganisms that influence each other and their metabolic activities or survival. One chemical produced by bacteria that influence algae is vitamin B12, an enzyme cofactor used for a variety of metabolic functions. The alga Chlamydomonas reinhardtii benefits from vitamin B12 produced by Sinorhizobium meliloti by producing the amino acid methionine under high temperatures which are required for Chlamydomonas thermotolerance. Yet, our understanding of this interaction under normal and stressful temperatures is poor. Here, we used quantitative proteomics to identify differentially expressed proteins to reveal metabolic adjustments made by Chlamydomonas and Sinorhizobium that could facilitate this mutualism. These findings will enhance our understanding of how photosynthetic algae and their associated microbiomes will respond as global temperatures increase.

Clickable tryptophan modification for late-stage diversification of native peptides

As the least abundant residue in proteins, tryptophan widely exists in peptide drugs and bioactive natural products and contributes to drug-target interactions in multiple ways. We report here a clickable tryptophan modification for late-stage diversification of native peptides, via catalyst-free C2-sulfenylation with 8-quinoline thiosulfonate reagents in trifluoroacetic acid (TFA). A wide range of groups including trifluoromethylthio (SCF3), difluoromethylthio (SCF2H), (ethoxycarbonyl)difluoromethylthio (SCF2CO2Et), alkylthio, and arylthio were readily incorporated. The rapid reaction kinetics of Trp modification and full tolerance with other 19 proteinogenic amino acids, as well as the super dissolving capability of TFA, render this method suitable for all kinds of Trp-containing peptides without limitations from sequences, hydrophobicity, and aggregation propensity. The late-stage modification of 15 therapeutic peptides (1.0 to 7.6 kilodaltons) and the improved bioactivity and serum stability of SCF3- and SCF2H-modified melittin analogs illustrated the effectiveness of this method and its potential in pharmacokinetic property improvement.

Fermentation Analytical Technology (FAT): Monitoring industrial E. coli fermentations using absolute quantitative 1H NMR spectroscopy

BACKGROUND

To perform fast, reproducible, and absolute quantitative measurements in an automated manner has become of paramount importance when monitoring industrial processes, including fermentations. Due to its numerous advantages - including its inherent quantitative nature - Proton Nuclear Magnetic Resonance (1H NMR) spectroscopy provides an ideal tool for the time-resolved monitoring of fermentations. However, analytical conditions, including non-automated sample preparation and long relaxation times (T1) of some metabolites, can significantly lengthen the experimental time and make implementation in an industrial set up unfeasible.

RESULTS

We present a high throughput method based on Standard Operating Procedures (SOPs) and 1H NMR, which lays the foundation for what we call Fermentation Analytical Technology (FAT). Our method was developed for the accurate absolute quantification of metabolites produced during Escherichia coli industrial fermentations. The method includes: (1) a stopped flow system for non-invasive sample collection followed by sample quenching, (2) automatic robot-assisted sample preparation, (3) fast 1H NMR measurements, (4) metabolites quantification using multivariate curve resolution (MCR), and (5) metabolites absolute quantitation using a novel correction factor (k) to compensate for the short recycle delay (D1) employed in the 1H NMR measurements. The quantification performance was tested using two sample types: buffer solutions of chemical standards and real fermentation samples. Five metabolites - glucose, acetate, alanine, phenylalanine and betaine - were quantified. Absolute quantitation ranged between 0.64 and 3.40 mM in pure buffer, and 0.71-7.76 mM in real samples.

SIGNIFICANCE

The proposed method is generic and can be straight forward implemented to other types of fermentations, such as lactic acid, ethanol and acetic acid fermentations. It provides a high throughput automated solution for monitoring fermentation processes and for quality control through absolute quantification of key metabolites in fermentation broth. It can be easily implemented in an at-line industrial setting, facilitating the optimization of the manufacturing process towards higher yields and more efficient and sustainable use of resources.

A Novel Non-Destructive Rapid Tool for Estimating Amino Acid Composition and Secondary Structures of Proteins in Solution

Amino-acid protein composition plays an important role in biology, medicine, and nutrition. Here, a groundbreaking protein analysis technique that quickly estimates amino acid composition and secondary structure across various protein sizes, while maintaining their natural states is introduced and validated. This method combines multivariate statistics and the thermostable Raman interaction profiling (TRIP) technique, eliminating the need for complex preparations. In order to validate the approach, the Raman spectra are constructed of seven proteins of varying sizes by utilizing their amino acid frequencies and the Raman spectra of individual amino acids. These constructed spectra exhibit a close resemblance to the actual measured Raman spectra. Specific vibrational modes tied to free amino and carboxyl termini of the amino acids disappear as signals linked to secondary structures emerged under TRIP conditions. Furthermore, the technique is used inversely to successfully estimate amino acid compositions and secondary structures of unknown proteins across a range of sizes, achieving impressive accuracy ranging between 1.47% and 5.77% of root mean square errors (RMSE). These results extend the uses for TRIP beyond interaction profiling, to probe amino acid composition and structure.

The effectiveness of selection in a species affects the direction of amino acid frequency evolution

Nearly neutral theory predicts that species with higher effective population size (N e ) are better able to purge slightly deleterious mutations. We compare evolution in high-N e vs. low-N e vertebrates to reveal which amino acid frequencies are subject to subtle selective preferences. We take three complementary approaches, two measuring flux and one measuring outcomes. First, we fit non-stationary substitution models of amino acid flux using maximum likelihood, comparing the high-N e clade of rodents and lagomorphs to its low-N e sister clade of primates and colugos. Second, we compare evolutionary outcomes across a wider range of vertebrates, via correlations between amino acid frequencies and N e . Third, we dissect the details of flux in human, chimpanzee, mouse, and rat, as scored by parsimony - this also enables comparison to a historical paper. All three methods agree on which amino acids are preferred under more effective selection. Preferred amino acids tend to be smaller, less costly to synthesize, and to promote intrinsic structural disorder. Parsimony-induced bias in the historical study produces an apparent reduction in structural disorder, perhaps driven by slightly deleterious substitutions. Within highly exchangeable pairs of amino acids, arginine is strongly preferred over lysine, and valine over isoleucine, consistent with more effective selection preferring a marginally larger free energy of folding. These two preferences match differences between thermophiles and mesophilic relatives. These results reveal the biophysical consequences of mutation-selection-drift balance, and demonstrate the utility of nearly neutral theory for understanding protein evolution.

The determinants of the rarity of nucleic and peptide short sequences in nature

The prevalence of nucleic and peptide short sequences across organismal genomes and proteomes has not been thoroughly investigated. We examined 45 785 reference genomes and 21 871 reference proteomes, spanning archaea, bacteria, eukaryotes and viruses to calculate the rarity of short sequences in them. To capture this, we developed a metric of the rarity of each sequence in nature, the rarity index. We find that the frequency of certain dipeptides in rare oligopeptide sequences is hundreds of times lower than expected, which is not the case for any dinucleotides. We also generate predictive regression models that infer the rarity of nucleic and proteomic sequences across nature or within each domain of life and viruses separately. When examining each of the three domains of life and viruses separately, the R² performance of the model predicting rarity for 5-mer peptides from mono- and dipeptides ranged between 0.814 and 0.932. A separate model predicting rarity for 10-mer oligonucleotides from mono- and dinucleotides achieved R² performance between 0.408 and 0.606. Our results indicate that the mono- and dinucleotide composition of nucleic sequences and the mono- and dipeptide composition of peptide sequences can explain a significant proportion of the variance in their frequencies in nature.

Metabolic immunity against microbes

Pathogens, including viruses, bacteria, fungi, and parasites, remodel the metabolism of their host to acquire the nutrients they need to proliferate. Thus, host cells are often perceived as mere exploitable nutrient pools during infection. Mounting reports challenge this perception and instead suggest that host cells can actively reprogram their metabolism to the detriment of the microbial invader. In this review, we present metabolic mechanisms that host cells use to defend against pathogens. We highlight the contribution of domesticated microbes to host defenses and discuss examples of host-pathogen arms races that are derived from metabolic conflict.

Revealing the comprehensive impact of organic compounds on the partial nitrification-anammox system during incineration leachate treatment: metabolic hierarchy and adaptation

Organics, as widespread pollutants in high-strength ammonia wastewater, typically exert adverse effects on the performance of partial nitrification-anammox (PNA) systems. However, the in-depth knowledge on how microbial consortia respond to these disturbances remains limited. In this study, we unveiled the evolution of complex organic matter flow and its impact on the metabolic hierarchy and adaptation of microbial consortia, employing multi-omics approaches, i.e., 16S amplicon sequencing, metagenomics, and metabolomics. In a two-stage PNA system sequentially treating synthetic wastewater and incineration leachate over 230 days, partial nitrification stayed stable (nitrite accumulation > 97%) while anammox efficiency dropped (nitrogen removal decreased from 86% to 78%). The phenomenon was revealed to be correlated with the evolution of dissolved organic matter (DOM) and xenobiotic organic compounds (XOCs). In the PN stage, ammonia-oxidizing bacteria (AOB) exhibited excellent adaptability through active metabolic regulation after treating leachate. Numerous heterotrophs proliferated to utilize DOM and XOCs, triggering a "boom" state evident in the glycerophospholipid metabolism. However, in the anammox stage, the competition between carbon fixation and central carbon metabolism within autotrophs and heterotrophs became evident. Increased biosynthesis costs inhibited the central metabolism (specific anammox activity decreased by 66%) and the Wood-Ljungdahl pathway of anammox bacteria (AnAOB) in the presence of recalcitrant organics. Additionally, the degradation of organics was limited, exhibiting a "bust" state. This study revealed the metabolic adaption and susceptibility of AOB and AnAOB in response to organics from the leachate, demonstrating the applicability of the two-stage configuration for treating high-strength wastewater containing abundant and diverse organics.

AI-Driven Spectral Decomposition: Predicting the Most Probable Protein Compositions from Surface Enhanced Raman Spectroscopy Spectra of Amino Acids

Surface-enhanced Raman spectroscopy (SERS) is a powerful tool for elucidating the molecular makeup of materials. It possesses the unique characteristics of single-molecule sensitivity and extremely high specificity. However, the true potential of SERS, particularly in capturing the biochemical content of particles, remains underexplored. In this study, we harnessed transformer neural networks to interpret SERS spectra, aiming to discern the amino acid profiles within proteins. By training the network on the SERS profiles of 20 amino acids of human proteins, we explore the feasibility of predicting the predominant proteins within the µL-scale detection volume of SERS. Our results highlight a consistent alignment between the model's predictions and the protein's known amino acid compositions, deepening our understanding of the inherent information contained within SERS spectra. For instance, the model achieved low root mean square error (RMSE) scores and minimal deviation in the prediction of amino acid compositions for proteins such as Bovine Serum Albumin (BSA), ACE2 protein, and CD63 antigen. This novel methodology offers a robust avenue not only for protein analytics but also sets a precedent for the broader realm of spectral analyses across diverse material categories. It represents a solid step forward to establishing SERS-based proteomics.

The shikimate pathway: gateway to metabolic diversity

Covering: 1997 to 2023The shikimate pathway is the metabolic process responsible for the biosynthesis of the aromatic amino acids phenylalanine, tyrosine, and tryptophan. Seven metabolic steps convert phosphoenolpyruvate (PEP) and erythrose 4-phosphate (E4P) into shikimate and ultimately chorismate, which serves as the branch point for dedicated aromatic amino acid biosynthesis. Bacteria, fungi, algae, and plants (yet not animals) biosynthesize chorismate and exploit its intermediates in their specialized metabolism. This review highlights the metabolic diversity derived from intermediates of the shikimate pathway along the seven steps from PEP and E4P to chorismate, as well as additional sections on compounds derived from prephenate, anthranilate and the synonymous aminoshikimate pathway. We discuss the genomic basis and biochemical support leading to shikimate-derived antibiotics, lipids, pigments, cofactors, and other metabolites across the tree of life.

High synthetic cost-amino acids reduce member interactions of acetate-degrading methanogenic microbial community

Introduction

The cooperation among members of microbial communities based on the exchange of public goods such as 20 protein amino acids (AAs) has attracted widespread attention. However, little is known about how AAs availability affects interactions among members of complex microbial communities and the structure and function of a community.

Methods

To investigate this question, trace amounts of AAs combinations with different synthetic costs (low-cost, medium-cost, high-cost, and all 20 AAs) were supplemented separately to acetate-degrading thermophilic methanogenic reactors, and the differences in microbial community structure and co-occurring networks of main members were compared to a control reactor without AA supplementation.

Results

The structure of the microbial community and the interaction of community members were influenced by AAs supplementation and the AAs with different synthetic costs had different impacts. The number of nodes, links, positive links, and the average degree of nodes in the co-occurrence network of the microbial communities with AAs supplementation was significantly lower than that of the control without AAs supplementation, especially for all 20 AAs supplementation followed by the medium- and high-cost AAs supplementation. The average proportion of positive interactions of microbial members in the systems supplemented with low-cost, medium-cost, high-cost, all AAs, and the control group were 0.42, 0.38, 0.15, 0.4, and 0.45, respectively. In addition, the ecological functions of community members possibly changed with the supplementation of different cost AAs.

Discussion

These findings highlight the effects of AAs availability on the interactions among members of complex microbial communities, as well as on community function.

Targeting imidazole-glycerol phosphate dehydratase in plants: novel approach for structural and functional studies, and inhibitor blueprinting

The histidine biosynthetic pathway (HBP) is targeted for herbicide design with preliminary success only regarding imidazole-glycerol phosphate dehydratase (IGPD, EC 4.2.1.19), or HISN5, as referred to in plants. HISN5 catalyzes the sixth step of the HBP, in which imidazole-glycerol phosphate (IGP) is dehydrated to imidazole-acetol phosphate. In this work, we present high-resolution cryoEM and crystal structures of Medicago truncatula HISN5 (MtHISN5) in complexes with an inactive IGP diastereoisomer and with various other ligands. MtHISN5 can serve as a new model for plant HISN5 structural studies, as it enables resolving protein-ligand interactions at high (2.2 Å) resolution using cryoEM. We identified ligand-binding hotspots and characterized the features of plant HISN5 enzymes in the context of the HISN5-targeted inhibitor design. Virtual screening performed against millions of small molecules not only revealed candidate molecules but also identified linkers for fragments that were experimentally confirmed to bind. Based on experimental and computational approaches, this study provides guidelines for designing symmetric HISN5 inhibitors that can reach two neighboring active sites. Finally, we conducted analyses of sequence similarity networks revealing that plant HISN5 enzymes derive from cyanobacteria. We also adopted a new approach to measure MtHISN5 enzymatic activity using isothermal titration calorimetry and enzymatically synthesized IGP.

The minimum energy required to build a cell

Understanding the energy requirements for cell synthesis accurately and comprehensively has been a longstanding challenge. We introduce a computational model that estimates the minimum energy necessary to build any cell from its constituent parts. This method combines omics and internal cell compositions from various sources to calculate the Gibbs Free Energy of biosynthesis independently of specific metabolic pathways. Our public tool, Synercell, can be used with other models for minumum species-specific energy estimations in any well-sequenced species. The energy for synthesising the genome, transcriptome, proteome, and lipid bilayer of four cell types: Escherichia coli, Saccharomyces cerevisiae, an average mammalian cell and JCVI-syn3A were estimated. Their modelled minimum synthesis energies at 298 K were 9.54 × 10 - 11 J/cell, 4.99 × 10 - 9 J/cell, 3.71 × 10 - 7 J/cell and 3.69 × 10 - 12 respectively. Gram-for-gram synthesis of lipid bilayers requires the most energy, followed by the proteome, genome, and transcriptome. The average per gram cost of biomass synthesis is in the 300s of J/g for all four cells. Implications for the generalisability of cell construction and applications to biogeosciences, cellular biology, biotechnology, and astrobiology are discussed.

Moderating the neutralist-selectionist debate: exactly which propositions are we debating, and which arguments are valid?

Half a century after its foundation, the neutral theory of molecular evolution continues to attract controversy. The debate has been hampered by the coexistence of different interpretations of the core proposition of the neutral theory, the 'neutral mutation-random drift' hypothesis. In this review, we trace the origins of these ambiguities and suggest potential solutions. We highlight the difference between the original, the revised and the nearly neutral hypothesis, and re-emphasise that none of them equates to the null hypothesis of strict neutrality. We distinguish the neutral hypothesis of protein evolution, the main focus of the ongoing debate, from the neutral hypotheses of genomic and functional DNA evolution, which for many species are generally accepted. We advocate a further distinction between a narrow and an extended neutral hypothesis (of which the latter posits that random non-conservative amino acid substitutions can cause non-ecological phenotypic divergence), and we discuss the implications for evolutionary biology beyond the domain of molecular evolution. We furthermore point out that the debate has widened from its initial focus on point mutations, and also concerns the fitness effects of large-scale mutations, which can alter the dosage of genes and regulatory sequences. We evaluate the validity of neutralist and selectionist arguments and find that the tested predictions, apart from being sensitive to violation of underlying assumptions, are often derived from the null hypothesis of strict neutrality, or equally consistent with the opposing selectionist hypothesis, except when assuming molecular panselectionism. Our review aims to facilitate a constructive neutralist-selectionist debate, and thereby to contribute to answering a key question of evolutionary biology: what proportions of amino acid and nucleotide substitutions and polymorphisms are adaptive?

Systems theory, thermodynamics and life: Integrated thinking across ecology, organization and biological evolution

In this paper we explore the relevance and integration of system theory and thermodynamics in terms of the Earth system. It is proposed that together, these fields explain the evolution, organization, functionality and directionality of life on Earth. We begin by summarizing historical and current thinking on the definition of life itself. We then investigate the evidence for a single unit of life. Given that any definition of life and its levels of organization are intertwined, we explore how the Earth system is structured and functions from an energetic perspective, by outlining relevant thermodynamic theory relating to molecular, metabolic, cellular, individual, population, species, ecosystem and biome organization. We next investigate the fundamental relationships between systems theory and thermodynamics in terms of the Earth system, examining the key characteristics of self-assembly, self-organization (including autonomy), emergence, non-linearity, feedback and sub-optimality. Finally, we examine the relevance of systems theory and thermodynamics with reference to two specific aspects: the tempo and directionality of evolution and the directional and predictable process of ecological succession. We discuss the importance of the entropic drive in understanding altruism, multicellularity, mutualistic and antagonistic relationships and how maximum entropy production theory may explain patterns thought to evidence the intermediate disturbance hypothesis.

Multilayered regulation of amino acid metabolism in Escherichia coli

Amino acid metabolism in Escherichia coli has long been studied and has established the basis for regulatory mechanisms at the transcriptional, posttranscriptional, and posttranslational levels. In addition to the classical signal transduction cascade involving posttranslational modifications (PTMs), novel PTMs in the two primary nitrogen assimilation pathways have recently been uncovered. The regulon of the master transcriptional regulator NtrC is further expanded by a small RNA derived from the 3´UTR of glutamine synthetase mRNA, which coordinates central carbon and nitrogen metabolism. Furthermore, recent advances in sequencing technologies have revealed the global regulatory networks of transcriptional and posttranscriptional regulators, Lrp and GcvB. This review provides an update of the multilayered and interconnected regulatory networks governing amino acid metabolism in E. coli.

Statistical analysis of synonymous and stop codons in pseudo-random and real sequences as a function of GC content

Knowledge of the frequencies of synonymous triplets in protein-coding and non-coding DNA stretches can be used in gene finding. These frequencies depend on the GC content of the genome or parts of it. An example of interest is provided by stop codons. This is relevant for the definition of Open Reading Frames. A generic case is provided by pseudo-random sequences, especially when they code for complex proteins or when they are non-coding and not subject to selection pressure. Here, we calculate, for such sequences and for all 25 known genetic codes, the frequency of each amino acid and stop codon based on their set of codons and as a function of GC content. The amino acids can be classified into five groups according to the GC content where their expected frequency reaches its maximum. We determine the overall Shannon information based on groups of synonymous codons and show that it becomes maximum at a percent GC of 43.3% (for the standard code). This is in line with the observation that in most fungi, plants, and animals, this genomic parameter is in the range from 35 to 50%. By analysing natural sequences, we show that there is a clear bias for triplets corresponding to stop codons near the 5'- and 3'-splice sites in the introns of various clades.