Plants are colonized by characteristic microbiomes that help maintain plant health and function. However, the mechanisms that make these communities assemble in a consistent, repeatable manner remain poorly understood. Here, we show how microbial metabolic strategies for host-derived substrates drive plant microbiome assembly, using a six-member synthetic community syncom that captures the taxonomic diversity of natural duckweed microbiome. Contrary to expectations of metabolic niche partitioning, five of six strains adopt similar metabolic states when colonizing the host alone, consistent with the preferential use of a shared substrate, acetaldehyde. In contrast, during competition with specific community members, these strains consistently switch toward alternative substrates, including sugars and aromatics. Strikingly, this metabolic switching accompanies all negative interspecies interactions observed in the community, indicating that a single class of metabolic response dominates the inhibitory interaction network organizing community structure. By comparison, although metabolite cross-feeding is widespread, its contribution to facilitative interactions depends on the background of resource competition. Together, these findings highlight competition-induced metabolic switching as a primary driver of microbial interaction networks, and provide a cross-scale account of how microbial metabolic strategies underpin the reproducible assembly of plant microbiomes.

Mechanoresponsive biomaterials are a revolutionary class of materials designed to respond dynamically to mechanical stimuli, providing tissue engineering and regenerative medicine with precise control over biological processes. Through processes including supramolecular interactions, strain stiffening, and force-induced conformational changes, these materials, which include hydrogels, elastomers, and piezoelectric composites, imitate the mechanics exclusive to biological tissues. Additionally, mechanoresponsive systems improve drug delivery by releasing drugs in response to pH changes or mechanical strain using various materials, including magnetic scaffolds and ultrasound-triggered micelles. Despite advancements in numerous arenas of biological sciences, problems with clinical translation, scalability, and long-term biocompatibility still exist. New developments combine technologies like 4D bioprinting to create dynamic, patient-specific scaffolds and artificial intelligence (AI)-assisted design to maximize material qualities. To achieve material innovation with the desired level of biological complexity, future initiatives should focus on multifunctional platforms that combine mechanical, electrical, and biochemical inputs at an advanced level. This review dives into several aspects of mechanoresponsive biomaterials by navigating through the fabrication methods, underlying principles, inception of these in biomedical applications, and progression through the current research settings.

Promoters are essential in transcriptional regulation, with the −10 and −35 boxes playing a critical role in determining their strength. Modulating these regions can effectively fine-tune promoter strength. However, the lack of a clear quantitative relationship between sequence composition and transcriptional output impedes the rational design of promoters. To address this, we developed a synthetic promoter library by varying RNA polymerase binding energies at the −10 and −35 boxes. The library was partitioned into four sublibraries with expression strengths spanning an 80-fold range. Using fluorescence-activated cell sorting FACS followed by sequencing, we identified 20,799 distinct promoters. Analysis of this library uncovered distinct sequence-activity patterns, including a small subset of −35 box sequences that consistently conferred high transcriptional output across diverse −10 partners. Based on this, we developed an artificial intelligence platform that integrates a convolutional neural network for strength prediction (Pearson’s r = 0.84) with a balanced generative adversarial network incorporating a gradient penalty for de novo promoter design. By coupling these models, we achieved a precise design of promoters with user-defined strengths (r = 0.85), establishing a bidirectional framework that links −10/–35 boxes to transcriptional activity through deep learning. This study expands the sequence diversity of functional −10 and −35 boxes in E. coli, provides a predictive platform for rational promoter engineering, and deciphers combinatorial motif interactions governing transcriptional regulation.

Bacteriophages must overcome host stress responses to replicate efficiently, yet how they engage with these pathways remains poorly understood. The bacterial stringent response (SR), mediated by the alarmone (p)ppGpp, globally suppresses metabolism and limits biosynthetic capacity, posing a potential barrier to phage infection. Here, we show that bacteriophage T7 directly counteracts the SR through its portal protein, Gp8. Using complementary genetic, biochemical, and infection assays, we demonstrate that Gp8 physically interacts with the (p)ppGpp synthetases RelA and SpoT, selectively inhibiting their synthetase activities and reducing intracellular (p)ppGpp levels during late infection. Disruption of this interaction delays host cell lysis and compromises phage replication, while elevated host (p)ppGpp levels impair infection efficiency. Remarkably, portal proteins from diverse E. coli phages share similar structural and functional properties, suggesting a conserved viral strategy to suppress the stringent response. Together, our findings uncover an unexpected regulatory role for phage portal proteins and reveal a conserved mechanism by which phages modulate bacterial stress physiology to optimize replication.

Functionalizing bacteria with magnetic nanoparticles (MNPs) is a common route toward magnetically responsive bacterial microrobots. However, existing strategies are often limited by low functionalization efficiency, weak binding, poor reproducibility, and nonspecific interactions. Here, we present a robust, specific, and reproducible magnetic functionalization platform based on the self-labeling protein HaloTag, yielding magnetic bacterial microrobots termed HaloBots. Using E. coli as an engineering host, HaloTag was displayed on the outer membrane via the Lpp OmpA anchoring system, with the assistance of a Long and Flexible (LF) peptide linker. Optimization of genetic engineering vectors and colony purification enabled robust and uniform HaloTag display across bacterial populations. In addition, MNPs were modified with chloroalkane PEG ligands to enable site-specific covalent conjugation with HaloTag. Tuning the ligand density on MNPs revealed a critical balance between ligand accessibility and surface charge for achieving efficient and specific attachment. Consequently, the resulting HaloBots exhibited stable MNP conjugation and reliable magnetic actuation. Collectively, this work establishes a modular and tunable strategy for engineering magnetically responsive bacterial microrobots.

Random variation in reproductive success--genetic drift--profoundly shapes genetic diversity and evolutionary trajectories. The strength of drift depends on the variance in descendant number, σd2, which governs key evolutionary outcomes: for instance, the establishment probability of a beneficial mutation scales inversely with σd2. However, whether σd2 itself evolves over long timescales has remained unclear, because allele-frequency fluctuations depend on drift only through the effective population size, Ne = N/σd2, which blends census population size with descendant-number variance. Here, we disentangle these components by using model-based Bayesian inference combined with joint tracking of (i) frequency fluctuations of neutrally barcoded lineages and (ii) census population sizes across growth cycles in the E. coli Long-Term Evolution Experiment. Analyzing 33 clones spanning the ancestor through 50,000 generations in two replicate populations (Ara-2 and Ara+2), we find that the strength of genetic drift evolved markedly--and divergently--between the two replicate populations. Both census size and σd2 changed substantially through time, with most variation in Ne driven by shifts in σd2 rather than census size. After approximately 2,000 generations, the σd2 of the two populations diverged sharply: Ara+2 generally remained close to a bottleneck-only null expectation, whereas Ara-2 exhibited 1.5-5x stronger drift, consistent with an evolved increase in stochasticity during growth. Because establishment probability scales as s/σd2, a beneficial mutation of given effect is roughly twice as likely to establish in Ara+2 as in Ara-2. Our results demonstrate that the key parameter governing genetic drift can itself evolve, with direct consequences for adaptation.

Sequence verification of plasmids is a fundamental process in synthetic biology. For plasmid sequence verification using next-generation sequencing (NGS) library preparation, Tn5 transposase is widely used. Streamlined sequencing workflow for laboratory-scale applications is important; however, recombinant Tn5 production in-house can be laborious. In this study, we demonstrated that the addition of a large soluble tag was not essential for purification and that the fusion of a His10 tag and protein A was sufficient to yield active Tn5 transposase in adequate amounts. In addition, we evaluated exonuclease-based genomic DNA digestion for plasmid sequencing from an E. coli lysate and the data analysis pipeline of sequences derived from the Illumina iSeq100 platform for de novo assembly, reference mapping, and annotation. This study proposes a simple workflow of an in-house easy-to-purify Tn5-based plasmid sequencing platform using a compact benchtop sequencer (AistSeq).

The biosynthetic production of human milk oligosaccharides through metabolic engineering has gained increasing attention in recent years. Yet, limited research has focused on the microbial synthesis of 3′-sialyllactosamine (3′-SLN), a critical intermediate for assembling sialyl Lewis X (sLex). In this work, a pathway enabling 3′-SLN biosynthesis was constructed in E. coli BL21(DE3). A key α2,3sialyltransferase (α2,3SiaT) from Bibersteinia trehalosi was identified and utilized to enhance the sialylation step toward 3′-SLN formation. To improve flux through the N-acetyllactosamine branch, essential genes were chromosomally integrated and overexpressed, while a CMP-N-acetylneuraminic acid synthesis module was coexpressed to secure an adequate donor supply. Furthermore, the expression balance was optimized through combinatorial adjustment of gene copy numbers and translational strength across modules. The engineered E. coli strain produced 0.78 g/L of 3′-SLN in shake-flask cultivation and further accumulated up to 7.75 g/L during 5-L fed-batch fermentation conditions, confirming the feasibility of microbial synthesis of 3′-SLN.