Biology subjects

Blaby, I. K.

Publications and source records attributed to Blaby, I. K..

7 recordsLinked to original sources

bioRxiv2025

TOR inhibition drives accumulation of amino acids through transcriptional activation in algae

Cellular homeostasis is maintained by the balance between energy production and breakdown and is fundamental to all forms of life. The conserved, ancient target of rapamycin (TOR) kinase is a central metabolic regulator in eukaryotes that integrates carbon and nitrogen to maintain homeostasis and promote growth and development through protein synthesis. While TOR regulatory mechanisms of amino acid accumulation are well known in yeast and mammals, they remain unknown in photosynthetic organisms. Here, we developed the unicellular green alga Chromochloris zofingiensis as a simpler model system for understanding TOR function. Multiomics experiments showed that TOR inhibition leads to an increase in amino acid levels independent of hexokinase-mediated glucose signaling. We observed upregulation of selective amino acid biosynthesis pathways at the transcript and protein levels as potential mechanisms driving the increase in amino acids. Transcriptomics and proteomics experiments identified a basic helix-loop-helix (bHLH) transcription factor with rapid upregulation during TOR inhibition. DAP-seq analysis demonstrated that bHLH can bind directly to the promoters of amino acid biosynthesis genes, potentially regulating their transcription in response to TOR inhibition. We found high conservation of the bHLH-binding motif in the genomes of other green algae and plants, suggesting a conserved regulatory mechanism for amino acid biosynthesis across Viridiplantae. Phosphoproteomics experiments also revealed novel conserved targets that are not currently recognized as part of the TOR pathway. Altogether, our findings elucidate the transcriptional regulation of amino acid metabolism and explain how TOR regulates nitrogen metabolism to support growth and development in photosynthetic organisms. Significance StatementCarbon and nitrogen metabolism play key roles in enhancing plant yield and reducing fertilizer use. Thus, improving nitrogen utilization can significantly boost crop productivity and algal biotechnology. From yeast to plants to mammals, the protein target of rapamycin (TOR) kinase is an essential metabolic regulator. Here, we developed the unicellular green alga Chromochloris zofingiensis as a simpler system to study conserved mechanisms in TOR signaling. Using a multiomics approach, we showed transcriptional regulation of amino acid accumulation upon TOR inhibition and identified a transcription factor with evolutionarily conserved DNA binding sites in nitrogen metabolism genes. We also discovered novel conserved targets of TOR. Our study demonstrates the role of TOR in regulating nitrogen metabolism to support growth and development in photosynthetic organisms.

plant biology↗

bioRxiv2025

Mining thermophile photosynthesis genes: a synthetic operon expressing Chloroflexota species reaction center genes in Rhodobacter sphaeroides

Photosynthesis is the foundation of the vast majority of life systems, and therefore the most important bioenergetic process on earth, and the greatest diversity in photosynthetic systems are found in microorganisms. However, understanding of the biophysical and biochemical processes that transduce light to chemical energy has derived from the relatively small subset of proteins from microbes that are amenable to cultivation, in contrast to the huge number of microbial DNA sequences encoding proteins that catalyze the initial photochemical reactions that has been deposited in databases, such as from metagenomics. We describe the use of a Rhodobacter sphaeroides laboratory strain for expression of heterologous photosynthesis genes to demonstrate the feasibility of mining this resource, focusing on hot spring Chloroflexota gene sequences. Using a synthetic operon of genes, we produced a photochemically active complex of reaction center proteins in our biological system. We also present bioinformatic analyses of anoxygenic type II reaction center sequences from metagenomic samples collected from hot (42-90{degrees} C) springs available through the JGI IMG database, to generate a resource of diverse sequences that potentially are adapted to photosynthesis at such temperatures. These data provide a view into the natural diversity of anoxygenic photosynthesis, through a lens focused on high-temperature environments. The approach we took to express such genes can be applied for potential biotechnology purposes as well as for studies of fundamental catalytic properties of these heretofore inaccessible protein complexes.

microbiology↗

bioRxiv2025

Biosensor-Driven Strain Engineering Reveals Key Cellular Processes for Maximizing Isoprenol Production in Pseudomonas putida

Synthetic biology tools have accelerated the generation of simple mutants, but combinatorial testing remains challenging. High-throughput methods struggle translating from proof-of-principle molecules to advanced bioproducts. We address this challenge with a biosensor-driven strategy for enhanced isoprenol production in Pseudomonas putida, a key precursor for sustainable aviation fuel and platform chemicals. This biosensor leverages P. putidas native response to short-chain alcohols via a previously uncharacterized hybrid histidine kinase signaling cascade. Refactoring the biosensor for a conditional growth-based selection enabled identification of competing cellular processes with a [~]16,500-member CRISPRi-library. An iterative combinatorial strain engineering approach yielded an integrated P. putida strain producing [~]900 mg/L isoprenol in glucose minimal medium, a 36-fold increase. Ensemble -omics analysis revealed metabolic rewiring, including amino acid accumulation as key drivers of enhanced production. Techno-economic analysis elucidated the path to economic viability and confirmed the benefits of adding amino acids outweigh the additional costs. This study establishes a robust biosensor driven approach for optimizing other heterologous pathways, accelerating microbial cell factory development. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=138 SRC="FIGDIR/small/643695v1_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@533605org.highwire.dtl.DTLVardef@ff98fforg.highwire.dtl.DTLVardef@9592fdorg.highwire.dtl.DTLVardef@1e52993_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2025

Genome-wide exploration of the transcriptional regulatory landscape in the early-diverging fungus R. microsporus reveals pervasive DNA methyl adenine regulatory network

Genetic regulation mechanisms rely on complex transcriptional networks that are often difficult to decipher. The study of transcription factor (TF) binding sites and their targets has traditionally faced scalability challenges, hindering comprehensive cistrome analyses. However, the development of the DNA affinity purification and sequencing (DAP-seq) technique has allowed unprecedented large-scale studies at genome-wide level of TF binding with high reproducibility. In this study, we apply this technique to the human opportunistic pathogen R. microsporus, a mucoralean fungus belonging to the understudied group of early-diverging fungi (EDF). We characterize genome-wide binding sites of 58 TFs encoded by genes regulated through adenine methylation and representing major TF families, representing the most extensive DAP-seq study in filamentous fungi. This analysis reveals their binding profiles and recognized sequences, expanding and diversifying the catalog of known fungal motifs. By integrating this data with DNA 6-methyladenine profiling, we uncover the extensive direct and indirect impact of this epigenetic modification on the regulation of gene expression. Furthermore, the generated data facilitates the identification and functional characterization of TFs involved in biologically relevant processes, such as zinc metabolism and light response, serving as a proof of concept for the utility of the DAP-seq data. These findings not only enhance our understanding of regulatory mechanisms in R. microsporus but also provide broader insights into gene regulation across the fungal kingdom.

genetics↗

bioRxiv2024

An atlas of conserved transcription factor binding sites reveals the cell type-resolved gene regulatory landscape of flowering plants

Transcription factors (TFs) are proteins that bind DNA to control where and when genes are expressed. In plants, dozens of TF families interact with distinct sets of binding sites (TFBSs) that reflect each TFs role in organismal function and species-specific adaptations. However, defining these roles and understanding broader patterns of regulatory evolution remains challenging, as predicted TFBSs may lack a clear impact on transcription, and experimentally-derived TF binding maps to date are modest in scale or restricted to model organisms. Here, we present a scalable TFBS assay that we leveraged to create an atlas of nearly 3,000 genome-wide binding site maps for 360 TFs in 10 species spanning 150 million years of flowering plant evolution. We find that TF orthologs from distant species retain nearly identical binding preferences, suggesting that regulatory evolution primarily arises from gain and loss of TFBSs. Within lineages however, conserved TFBSs are over-represented and found in regions harboring signatures of functional regulatory elements. Moreover, genes with conserved TFBSs showed a striking enrichment for cell type-specific expression in single-nuclei RNA atlases, providing a robust marker of each TFs activity and developmental role. Finally, we compare distant lineages, illustrating how ancient regulatory modules were recruited and rewired to enable adaptations underlying the evolutionary success of grasses.

genomics↗

bioRxiv2024

Enzymatic carbon-fluorine bond cleavage by human gut microbes

Fluorinated compounds are used for agrochemical, pharmaceutical, and numerous industrial applications, resulting in global contamination. In many molecules, fluorine is incorporated to enhance the half-life and improve bioavailability. Fluorinated compounds enter the human body through food, water, and xenobiotics including pharmaceuticals, exposing gut microbes to these substances. The human gut microbiota is known for its xenobiotic biotransformation capabilities, but it was not previously known whether gut microbial enzymes could break carbon-fluorine bonds, potentially altering the toxicity of these compounds. Here, through the development of a rapid, miniaturized fluoride detection assay for whole-cell screening, we discovered active gut microbial defluorinases. We biochemically characterized enzymes from diverse human gut microbial classes including Clostridia, Bacilli, and Coriobacteriia, with the capacity to hydrolyze (di)fluorinated organic acids and a fluorinated amino acid. Whole-protein alanine scanning, molecular dynamics simulations, and chimeric protein design enabled the identification of a disordered C-terminal protein segment involved in defluorination activity. Domain swapping exclusively of the C-terminus conferred defluorination activity to a non-defluorinating dehalogenase. To advance our understanding of the structural and sequence differences between defluorinating and non-defluorinating dehalogenases, we trained machine learning models which identified protein termini as important features. Models trained on 41-amino acid segments from protein C-termini alone predicted defluorination activity with 83% accuracy (compared to 95% accuracy based on full-length protein features). This work is relevant for therapeutic interventions and environmental and human health by uncovering specificity-determining signatures of fluorine biochemistry from the gut microbiome. SignificanceHumans have introduced carbon-fluorine bonds into numerous manufactured compounds, including pharmaceuticals, leading to the formation of toxic fluorinated byproducts. While the human gut microbiota is known for its ability to metabolize drugs, its encoded capacity to break the strong carbon-fluorine chemical bond was previously unknown. Here we discovered that human gut microbial enzymes are capable of cleaving carbon-fluorine bonds. We developed a 96-well colorimetric fluoride assay amenable to bacterial culture-based screening. We additionally conducted whole-protein alanine scanning mutagenesis and identified through machine learning that flexible C-terminal loop residues were predictive of defluorination. Taken in the context of flexible regions of other enzyme families known to perform fluorine chemistry, this work supports using convergent structural features to predict defluorination specificity.

biochemistry↗

bioRxiv2018

ManiNetCluster: A Manifold Learning Approach to Reveal the Functional Linkages Across Multiple Gene Networks

The coordination of genome encoded function is a critical and complex process in biological systems, especially across phenotypes or states (e.g., time, disease, organism). Understanding how the complexity of genome-encoded function relates to these states remains a challenge. To address this, we have developed a novel computational method based on manifold learning and comparative analysis, ManiNetCluster, which simultaneously aligns and clusters multiple molecular networks to systematically reveal function links across multiple datasets. Specifically, ManiNetCluster employs manifold learning to match local and non-linear structures among the networks of different states, to identify cross-network linkages. By applying ManiNetCluster to the developmental gene expression datasets across model organisms (e.g., worm, fruit fly), we found that our tool significantly better aligns the orthologous genes than existing state-of-the-art methods, indicating the non-linear interactions between evolutionary functions in development. Moreover, we applied ManiNetCluster to a series of transcriptomes measured in the green alga Chlamy-domonas reinhardtii, to determine the function links between various metabolic processes between the light and dark periods of a diurnally cycling culture. For example, we identify a number of genes putatively regulating processes across each lighting regime, and how comparative analyses between ManiNetCluster and other clustering tools can provide additional insights. ManiNetCluster is available as an R package together with a tutorial at https://github.com/namtk/ManiNetCluster.

bioinformatics↗