In response to environmental changes, bacteria have evolved sophisticated regulatory networks that incorporate small RNAs (sRNAs) and transcription factors (TFs) to fine-tune cellular physiology. Both sRNAs and TFs modulate gene expression, but the former function via post-transcriptional mechanisms, while the latter act at the transcriptional level. However, it remains unclear why both regulatory layers are conserved through evolution, rather than one being sufficient. Here, we experimentally identified that CRP, a global regulator, regulates 25 small RNAs (sRNAs) in Escherichia coli. Interestingly, CRP also controls 80% of the target genes of these sRNAs. This architecture led us to identify 34 novel sRNA-mediated feed-forward loops (sFFLs) circuits where CRP regulates both an sRNA and its target within the CRP regulon. Quantitative PCR analysis of 16 such sFFLs revealed that each type possesses a distinct cAMP dose-response profile, suggesting that different sFFL structures embody unique regulatory logic. Specifically, coherent and incoherent type 3 and 4 sFFLs exhibit broader dynamic ranges in their dose-response compared to open-loop controls. Coherent and incoherent type 1 and 2 sFFLs appear more energy-efficient. Altogether, we propose that sRNAs cooperate with TFs through sFFLs to optimize both the energy efficiency and the diversity of signal response profiles. Therefore, sRNAs serve as critical components integrating transcriptional and post-transcriptional networks across diverse cellular pathways.

Antibiotics revolutionized medicine in the 20th century by drastically reducing mortality from bacterial infections. However, their effectiveness is threatened by the global rise of antimicrobial resistance (AMR), driven by misuse, overuse, and environmental dissemination. This review explores the historical trajectory of antibiotics, the mechanisms of bacterial resistance, and the urgent need for innovation amid a declining antibiotic development pipeline. Herein, we highlight the scientific and economic barriers that have discouraged investment by major pharmaceutical companies and examine emerging strategies to address this crisis. Key advances in microbial bioprospecting, including cultivation improvement techniques and genome mining, are discussed alongside the role of high-throughput sequencing and bioinformatics in unlocking the metabolic potential of uncultivated microorganisms. Particular emphasis is placed on the integration of artificial intelligence and machine learning to accelerate drug discovery, predict antimicrobial activity, and identify resistance genes. Additionally, we present alternative therapeutic strategies beyond traditional antibiotics, such as phage therapy, antimicrobial peptides, quorum sensing inhibitors, synthetic conjugates, and vaccine development. Together, these interdisciplinary approaches offer promising pathways to revitalize the antimicrobial pipeline and address the growing threat of antibiotic resistance.

Lactoferrin (LF) plays a positive role in attenuating aging. In this study, LF obtained using different processing methods (freeze-dried: F and spray-dried: S) and its gastrointestinal digesta (XF and XS) were supplemented in d-gal-induced mice to explore their antiaging effects. The results showed that LF and its digesta (LFs) effectively ameliorated cognitive decline. Mechanistically, LFs prevented neuronal and synaptic injury by restoring redox balance, inhibiting the activation of microglia and astrocytes, and activating the cAMP-response element binding protein (CREB)/brain-derived neurotrophic factor (BDNF) pathway. Additionally, LFs increased the tight junction proteins and mucin-2, regulated the gut microbiota, particularly enriching bacteria in Firmicutes and restoring the Firmicutes/Bacteroidota ratio to maintain intestinal homeostasis. Meanwhile, LFs altered phospholipids (PLs) and other metabolites involved in glycerophospholipid metabolism such as arachidonic acid. Correlation analysis showed a significant association among metabolites, microbiota, and behaviors. These results indicated that LF and especially its digesta exert antiaging effects through multitarget pathways involving neuronal protection, neuroinflammation suppression, and microbiota–gut–brain axis regulation.

Rubisco catalyzes the CO2 fixation step in the dark reactions of photosynthesis. Transgenic expression of better-performing Rubisco orthologs in plants or discovery of improved mutants of Rubisco via protein engineering could theoretically accelerate plant growth and improve crop yields. However, efforts to heterologously express or engineer Rubisco are frequently stymied by the chaperone-dependent folding and assembly of the Rubisco holoenzyme, a process that can be disrupted by changes to Rubisco’s sequence. Elucidation of the effects that alterations to Rubisco’s sequence impose upon its biogenesis is hampered by reliance upon low-throughput methods for verification of Rubisco assembly. Here, we report the engineering of a genetically encoded biosensor to sense the assembly of Form I Rubiscos in E. coli. We show that the biosensor can detect the RbcS-dependent assembly of cyanobacterial Rubisco orthologs, the formation of chaperone-stabilized RbcL oligomeric assembly intermediates, and differences in assembly caused by mutations to the RbcL sequence. Additionally, we perform a large-scale examination of the relative assembly levels of a ∼7500-member Halothiobacillus neapolitanus RbcL mutant library by adapting the biosensor for use with phage-assisted noncontinuous selection. Our experiment predicts that the majority (>90%) of examined RbcL mutations exert a negative effect on assembly, lending support to the hypothesis that Rubisco biogenesis constrains both its natural evolution and improvement by protein engineering.

Recombinant adeno-associated viral (rAAV) vectors are a leading platform for in vivo gene therapy, valued for their excellent safety, broad serotype diversity, and scalable production. Targeted delivery through capsid display of ligands holds great promise, yet current retargeting strategies often rely on extensive capsid re-engineering and restrict the use of ligands incompatible with intracellular expression systems. Here, we present a modular AAV retargeting platform that, for the first time, employs the SpyTag/SpyCatcher system via genetic integration into the AAV2 capsid. SpyTag is a small peptide that forms a covalent, irreversible bond with its protein partner, SpyCatcher, allowing site-specific ligand coupling under physiological conditions. Inserting SpyTag into surface-exposed capsid sites enabled postassembly functionalization of AAVs with SpyCatcher-fused targeting proteins. As proof of concept, we used SpyCatcher fusions with designed ankyrin repeat proteins (DARPins) specific for EGFR, EpCAM, and HER2. This conferred highly specific transduction of corresponding cancer cell lines with minimal off-target activity. Therapeutic potential was demonstrated by delivering a suicide gene, inducing selective cancer cell killing upon prodrug administration. This “one-fits-all” platform allows rapid and flexible retargeting without significantly altering the underlying vectors genome or production process. It supports the incorporation of large or complex ligands not amenable to genetic fusion and facilitates high-throughput preclinical evaluation strategies. By uniting capsid engineering with modular ligand display, our approach provides a scalable and versatile framework for precision gene delivery, broadening the applicability of rAAV in both therapeutic and discovery settings.

Transposon mutagenesis enables genome-wide interrogation of gene function with a single self-contained genetic construct. However, its application to non-model bacteria remains limited because transposition efficiency depends on multiple host factors that are difficult to predict a priori including transposase activity, antibiotic resistance marker performance, and regulatory element compatibility. Here, we present a scalable system to identify functional transposon configurations in non-model bacteria through pooled library screening. We selected 18 promoters across multiple bacterial phyla to independently drive expression of the transposase and antibiotic resistance marker, generating 324 promoter combinatorial variants for each of six antibiotic resistance markers. We developed a high-throughput, automated workflow to deliver all 1,944 mariner-based transposon variants in a single experiment and applied this to 92 non-model bacteria spanning multiple phyla. From this, we identified functional transposons for 43 strains, with high-level mutagenesis (102-104 unique insertions) in 13 species, including seven with no previously described transposon mutagenesis. We then expanded to a dual-transposase system, mariner or Tn5, and devised a single transposon insertion sequencing method for high-throughput screening of 3,888 configurations. To demonstrate the practical utility of our screening approach, we used a top-performing variant to generate a genome-wide transposon mutant library for Comamonas testosteroni KF-1, a bacterium that metabolizes plastic- and lignin-derived polymers. We assayed this C. testosteroni mutant library to identify enzymatic pathways, transporter genes, and regulators essential for the metabolism of plastics-associated monomer terephthalate and lignin-associated monomer 4-hydroxybenzoate. Together, this work establishes a scalable approach to construct and identify genetic perturbation systems in non-model bacteria, expanding our ability to systematically probe gene function across the bacterial tree of life.

Disruption of protein–protein interactions (PPIs) is a major mechanism of a variant's deleterious effect. Computational tools are needed to assess such variants at scale, yet existing predictors rarely consider loss of specific interactions, particularly when variants perturb binding interfaces without significantly affecting protein stability. To address this problem, we present MutPred-PPI, a graph attention network that predicts interaction-specific (edgetic) effects of missense variants by operating on AlphaFold 3-based protein complex contact graphs with protein language model embeddings imposed upon nodes. We systematically evaluated our model with stringent group cross-validation as well as benchmark data recently collected within the IGVF Consortium. MutPred-PPI outperformed all baseline methods across all evaluation criteria, achieving an AUC of 0.85 on seen proteins and 0.72 on previously unseen proteins in cross-validation, demonstrating strong generalizability despite scarce training data. To demonstrate biomedical relevance, we applied MutPred-PPI to variants from ClinVar, HGMD, COSMIC, gnomAD, and two de novo neurodevelopmental disorder-linked datasets. Disease-associated variants from ClinVar and HGMD showed strong enrichment for both quasi-null and edgetic effects, whereas population variants from gnomAD increasingly preserved interactions with higher allele frequencies. Notably, we observed a strong edgetic disruption signature in highly recurrent cancer variants from both the full COSMIC dataset and a subset of variants from oncogenes. Recurrent tumor suppressor gene variants and autism spectrum disorder-associated variants exhibited moderate quasi-null enrichment, whilst neurodevelopmental disorder-linked variants showed a weak edgetic disruption signature. These results indicate distinct PPI perturbation mechanisms across disease types and show that MutPred-PPI captures functionally relevant molecular effects of pathogenic variants.

Reengineering translation initiation provides a powerful route to develop new translation systems that enable precise control of protein synthesis. While many engineered translation systems show promise, their orthogonality and impact on host physiology is largely uncharacterized, limiting broader application. Here, we develop an initiator-tRNA with an AAC anticodon mutation (i-tRNA-AAC), enabling translation initiation at a GUU start codon. Using fluorescence assays, proteomics, and tRNA sequencing, we assess the i-tRNA-AAC initiation orthogonality and effects on the host, guiding the optimization of its translational efficiency. We find the i-tRNA-AAC mutant initiates translation exclusively from its GUU start codon and is improved by overexpression of valyl-tRNA synthetase and methionyl-tRNA formyltransferase. However, this intervention perturbs aminoacylation and base modifications of endogenous tRNAs along with proteome-wide changes likely due to increased valine demand. Our findings demonstrate how an orthogonal translation initiation system reshapes host physiology and reveals the adaptive responses that accompany translational reprogramming.

The development of robust, food-grade microbial chassis with tailored metabolic functions is critical for advancing synthetic biology applications in health and nutrition. Here, we report a dual genome engineering strategy that integrates CRISPR-Cas9-mediated knock-in with Cre/loxP-driven genome reduction to streamline the genome of Lactococcus lactis NZ9000 and enable stable expression of a high-activity uricase variant. The resulting strain, NZ9000::UAT-ΔD6, demonstrated enhanced enzymatic performance in vitro, achieving 2.34 U/mL activity and complete degradation of ∼500 μM urate within 20 h. Beyond improved catalytic output, this dual-system approach established a genetically stable and biosafe probiotic chassis with moderate colonization capacity in the murine gut. The integration of CRISPR-Cas and Cre/loxP techniques in this work is intended to enhance the expression of heterologous genes in the chassis strain, while providing a versatile platform for the rational design of food-grade probiotics and offering a general strategy for constructing living biotherapeutic agents with targeted metabolic activities.