Topic: amino acids

Staphylococcus aureus metabolic requirements during skin colonization

Project Summary Staphylococcus aureus causes 76% of all skin infections, and yet simultaneously this pathogen asymptomatically colonizes the skin of 8-22% of healthy adults. Since the majority of S. aureus disease is the result of autoinfection from the colonizing strain, and invasive infections often originate from the skin, there is an urgent need to understand colonization mechanisms. In colonizing the skin, S. aureus encounters abundant levels of amino acid derivatives like urocanic acid and 5-oxoproline (OP) that contribute to the skin’s “acid mantle” and have reported anti-Staphylococcal properties. The central hypothesis of this project is that amino acid transport and catabolism is a critical feature of S. aureus skin colonization. To model this environment, we developed a skin-like media (SLM) to assess S. aureus physiology on the human skin surface. We determined the S. aureus transcriptional response using RNAseq and performed metabolomics in SLM, both of which demonstrated that amino acid catabolism genes are upregulated and that amino acids are rapidly consumed. These findings indicate that S. aureus has a skin expression program that enables survival and growth in this harsh environment. In Specific Aim 1, we are investigating S. aureus metabolism of serine, the second most abundant amino acid on human skin. We hypothesize that serine transport and catabolism is critical for S. aureus skin colonization. We will assess growth of mutant strains disrupted in serine pathways in the SLM and during mouse skin colonization. With 13C-tracing experiments we will investigate serine flux in S. aureus using metabolomics. We will determine serine transport mechanisms using bioinformatic guided targets and serine analogues. In Specific Aim 2, we will assess S. aureus resistance to toxic skin metabolites. OP is abundant on human skin and is known to be deleterious to bacteria. Our preliminary metabolomics studies indicate that S. aureus metabolizes OP in SLM, and we have identified a putative oxoprolinase (genes SAUSA300_1566-1561) that is upregulated on skin. We hypothesize that the detoxification of OP contributes to S. aureus survival on the skin. We will construct mutants in the 1566-1561 locus and test their contributions to OP metabolism in SLM with growth and metabolomics experiments. We will also investigate OP transport and test mutant strains in our mouse skin colonization model. In Specific Aim 3, we will identify new determinants of S. aureus skin colonization using TnSeq. We have developed an improved TnSeq library preparation and analysis protocol, and in our preliminary studies we performed TnSeq in SLM and in our mouse skin colonization model. We will evaluate pathway hits, such as respiration and fermentation, and aspartate metabolism targets by testing constructed mutants during SLM growth and in the mouse model. Novel hits will be validated with follow-up genetic experiments and 13C-tracing experiments. Collectively, the proposed studies will advance our knowledge of S. aureus colonization and adaptation to the skin environment.

AI-enabled methods for de novo design of functional peptides

PROJECT SUMMARY Macrocyclic peptides offer unique therapeutic potential, particularly for targeting intracellular protein-protein interactions considered ‘undruggable’ with traditional therapeutic modalities. Additionally, peptides can combine the benefits and bridge the gap between conventional small molecule therapeutics and large biologics. However, developing new peptide-based therapeutics using traditional approaches, such as natural product discovery or high-throughput library screening, has remained slow and challenging. Moreover, these conventional approaches cover a small fraction of the chemical and structural space, are restricted to a few starting peptide scaffolds, and typically fail to optimize for multiple therapeutic properties simultaneously. Our central hypothesis is that structure-guided deep learning methods can rapidly explore the chemical and structural space beyond natural products and enable precise, rapid, and custom design of functional peptides simultaneously optimized for target binding, selectivity, and membrane permeability. In our recent work, we developed physics-based methods for designing constrained peptides and macrocycles and, more recently, introduced deep learning methods for structure prediction, sequence redesign, and de novo design of peptide monomers and targeted binders. Here, we propose to develop a new generation of structure-guided deep learning (DL) tools to address the current limitations of computational and experimental methods and enable accurate, accessible, and broadly applicable design of macrocycles. Specifically, we will pursue the projects focused on: (i) leveraging DL methods to systematically enumerate the chemical and structural space of constrained peptides and membrane-traversing peptides to develop scaffolds and core design principles for functional peptide design; (ii) high-throughput design and data collection to improve design selection, filtering metrics, and sequence design algorithms; (iii) developing generative DL methods that expand beyond current capabilities and allow sequence and structure design with vast chemical space of non-canonical amino acids; and (iv) use those new generative methods to design macrocyclic binders against different therapeutically-relevant targets, including the critical fusion and attachment proteins from viruses of pandemic concern. Our preliminary work in these proposed areas demonstrates the feasibility of this approach. The proposed computational tools, scaffold sets, and designed peptides will significantly advance therapeutic design beyond the state-of-the-art and enable rapid and custom design of drug- like peptides tailored for addressing complex therapeutic, diagnostic and research challenges.

Metabolic Remodelling in the Developing Forebrain in Health and Disease

Little is known about the critical metabolic changes that neural cells have to undergo during development and how temporary shifts in this program can influence brain circuitries and behavior. Motivated by the identification of autism-associated mutations in SLC7A5, a transporter for metabolically essential large neutral amino acids (LNAAs), we utilized metabolomic profiling to investigate the metabolic states of the cerebral cortex across various developmental stages. Our findings reveal significant metabolic restructuring occurring in the forebrain throughout development, with specific groups of metabolites exhibiting stage-specific changes. Through the manipulation of Slc7a5 expression in neural cells, we discovered an interconnected relationship between the metabolism of LNAAs and lipids within the cortex. Neuronal deletion of Slc7a5 influences the postnatal metabolic state, resulting in a shift in lipid metabolism and a cell-type-specific modification in neuronal activity patterns. This ultimately gives rise to enduring circuit dysfunction.

Towards resolving the Protein Paradox in longevity and late-life health

Reducing protein intake (and that of key amino acids) extends lifespan, especially during mid-life and early late-life. Yet, due to a powerful protein appetite, reducing protein in the diet leads to increased food intake, promoting obesity – which shortens lifespan. That is the protein paradox. In the talk I will bring together pieces of the jigsaw, including: specific nutrient appetites, protein leverage, macronutrient interactions on appetite and ageing, the role of branched-chain amino acids and FGF-21, and then I will conclude by showing how these pieces fit together and play out in the modern industrialised food environment to result in the global pandemic of obesity and metabolic disease.

LACK OF SINGLE AMINO ACIDS TRANSCRIPTIONALLY TUNES SENSORY SYSTEMS TO ENHANCE MICROBIOTA INTAKE

FENS Forum 2026

Extracellular proteins – a source of amino acids for human glioblastoma cells

The metabolism of essential amino acids by human glioblastomas

Novel mechanism of hypoxic neuronal damage mediated by non-excitatory amino acids and astroglial swelling