Chemotaxis is the directional motion of objects in response to chemical gradients, a process that drives navigation in micro/nanomotors, enabling a bio-inspired transition toward autonomous direction control. However, current studies lack consistent mechanistic justification, definition, and standardized experimental validation. This review summarizes key physical principles governing active chemotaxis, surveys experimental strategies for generating chemical gradients and quantifying responses, and examines how individual chemotactic mechanisms and long-range, anisotropic chemical interactions give rise to emergent collective behaviors, while outlining prospective applications. Together, these efforts establish a principled engineering framework for advancing chemotaxis as a robust functional navigation modality in synthetic micro/nanomotors. This Review Article examines artificial chemotaxis in micro/nanomotors, detailing mechanisms, experimental strategies, and collective behaviors. It highlights the need for standardized validation and explores applications in biomedical and industrial fields, emphasizing the challenges and potential of synthetic chemotaxis.

Gram staining has guided microbiology for over a century by coloring cells purple or pink, a read-out thought to distinguish monoderms (single membrane, thick peptidoglycan) from diderms (inner and outer membranes with thin wall). Here we show this rule fails repeatedly across Bacillaceae lineages historically deemed “Gram-positive”. By combining light and transmission-electron microscopy, antibiotic-sensitivity assays and comparative genomics across 57 strains, we identify “Gram-negative-staining monoderms” lacking outer membrane yet retaining thick peptidoglycan walls. These bacteria lack lipopolysaccharide- and β-barrel assembly-genes and remain highly susceptible to vancomycin and lysozyme (agents normally excluded by diderm envelopes), demonstrating functional monoderm status. Surprisingly, teichoic-acid biosynthetic pathways are patchily distributed and do not predict staining behavior. This discovery calls into question the textbook purple-or-pink dichotomy, decoupling stain color from membrane architecture. Clinically, misidentifying pink-staining Bacillaceae (including emerging pathogens such as Bacillus infantis) risks inappropriate therapy, whereas genome-guided diagnostics enable precise antibiotic stewardship. Genomic and microscopy evidence shows that the Bacillaceae, assumed to only stain Gram-positive, actually have some lineages staining Gram-negative, yet unexpectedly maintaining a thick wall and no outer membrane, challenging Gram staining assumptions.

The efficient extraction of electrons from photosynthetic microorganisms remains a critical challenge in living biophotovoltaics (BPV). While nanomaterials can facilitate electron transport, their stochastic adsorption leads to inefficient material-wasteful interfaces. Here, we demonstrate a controllable approach to direct the targeted assembly of gold nanoparticles (AuNPs) onto the type IV pili of Synechocystis sp. PCC 6803 by using a genetically encoded gold-binding peptide. This approach creates a spatially precise conductive nano-bio interface on the cell envelope that serves as a dedicated electron conduit between photosynthetic electron transport chains (PETCs) and electrodes. This nano-bio interface enhances electron transfer through synergistic improvements in interfacial charge transfer and biofilm density, ultimately yielding a four-fold increase in photocurrent density, while using two orders of magnitude less gold than non-targeted strategies. Moreover, the AuNPs can be transferred from inactivated to fresh cells, indicating a potential pathway for long-term stability. This work establishes a generalizable strategy for the rational design of conductive interfaces on living cells, with implications for biophotovoltaics, microbial electrosynthesis, and next-generation biohybrid devices. Inefficient extracellular electron transfer of cyanobacteria impedes power output in biophotovoltaics. Here, the authors assemble a gold conductive layer on the cell surface by attaching gold-binding peptide to the pili structure, achieving a four-fold increase in photocurrent generation.

The extent to which an RNA folds into structure ensembles and how different structures in the ensemble regulate eukaryotic gene expression is not fully understood. Here, we coupled chemical probing with direct RNA sequencing to identify structure modifications along a single RNA molecule (sm-PORE-cupine). We used direct signal alignment in addition to base mapping to increase the percentage of mappable sequences and showed that Bernoulli mixture model clustering can separate structure ensembles accurately. We applied sm-PORE-cupine to identify isoform-specific structure ensembles along the SARS-CoV-2 genome and structure ensembles in the Candida albicans transcriptome. We observed that RNAs are more structurally homogeneous in vitro, at higher temperatures and in the 3′ untranslated regions of C. albicans. Structure ensembles are associated with changes in translation efficiency and decay in C. albicans, and we validated translation changes using reporter assays. sm-PORE-cupine expands the existing toolbox for studying RNA structure and function in diverse transcriptomes. sm-PORE-cupine combines SHAPE-based chemical probing with nanopore-based direct RNA sequencing to identify RNA structural ensembles in the SARS-CoV-2 genome and the Candida albicans transcriptome.

Freshwater lakes are globally significant sources of potent greenhouse gases (GHGs), but how their GHGs emissions respond to changing nutrient levels remains unclear. Here, we demonstrated that nitrous oxide (N2O) production pathways in lake sediments are tightly linked to trophic state, whereas methane (CH4) production appears to be multifactorial Through global metagenomics and controlled batch experiments. In eutrophic sediments, N2O is efficiently removed through complete denitrification, with nitrification serving as the main production pathway, whereas oligotrophic sediments produce N2O primarily via incomplete denitrification. By simulating nutrient transitions using a cross-inoculation experiment, we further revealed that lake sediments systematically shift between these N2O production pathways as their trophic state changes, from denitrification-driven to nitrification-dominated during eutrophication, with the inverse pattern during oligotrophication. Consequently, N2O emissions can be effectively mitigated by inhibiting nitrification in eutrophic lakes and restricting incomplete denitrification in oligotrophic ones. Our findings establish trophic status as a key driver of N2O production sources in lake sediments. Trophic status is a critical regulator of N2O dynamics in freshwater lake sediments, with implications for predicting GHG fluxes under global change scenarios.

The Gut microbiome-virome dynamics and interactions Collection highlights gut viruses, mainly bacteriophages, as determinants of microbial community structure and host-relevant functions across human, animal, and environmental systems. The Collection welcomes studies that quantify virus-microbe interactions, evidence-based linking viruses to microbial hosts, characterise infection dynamics, and connect them to ecological or clinical outcomes. It prioritises methodological rigour and translational relevance in diagnostics, surveillance, and phage-based interventions.

Gene expression analysis has evolved substantially over the past 25 years, from early transcript surveys using expressed sequence tags and microarrays to RNA sequencing, and more recently to single-cell and spatial transcriptomics. These successive waves have expanded measurement scale and resolution, enabling systematic discovery of transcriptional programmes, inference of gene regulatory networks, and increasingly direct links between transcriptomic insight and therapeutic strategies that modulate gene expression. In this Perspective, we synthesize major methodological milestones with bibliometric trends in leading bioinformatics journals to describe four revolutions that redefined gene expression analysis. We also map widely used computational tools onto a common timeline by analysing 70 78 831 open-access full-text articles, illustrating how enduring statistical frameworks coexist with rapidly growing end-to-end analysis ecosystems. We highlight current challenges and emerging directions in core bioinformatics approaches for gene expression analysis. Looking ahead, we argue that the next era will be defined less by generating new datasets and more by organizing, searching, and reusing transcriptomic and multimodal information at scale. We propose three future directions: consortium-scale searchable transcriptomic knowledgebases, foundation models for gene expression analysis, and programmable regulatory design for engineered control of gene expression. The landscape of gene expression analysis is shifting from descriptive measurement towards queryable, predictive, and programmable gene expression biology.

Microbial coexistence in complex communities requires mechanisms that minimize competition and optimize resource use. However, the mechanisms by which these ecological strategies are executed remain poorly understood. Here we show that bacteria modulate protein abundance in response to specific community members, reducing functional redundancy and promoting metabolic complementarity. Using synthetic gut-derived consortia exposed to distinct carbon sources, we systematically profiled proteomic responses of individual species across isolate, pairwise and 4-member communities. We found that biotic interactions, rather than abiotic conditions, were the dominant drivers of proteomic variation. These interactions led to reproducible, partner-specific expression shifts that significantly reduced functional overlap and were frequently associated with increased community productivity. Together, these findings highlight gene expression as a means by which microbes implement ecological strategies in community contexts. Through this regulatory plasticity, microbes dynamically reshape their realized niche through protein abundance modulation, enabling them to partition metabolic space and stabilize community structure. Biotic interactions modulate protein abundance, reducing functional redundancy and increasing productivity in complex bacterial communities.

RNA binding proteins (RBPs) are multi-faceted proteins that interact with transcripts in various RNA driven processes and functions. However, in situ covalent capture techniques for screening authentic RNA substrates of RBPs remain challenging in terms of reproducibility, specificity, and sensitivity. Here, we developed CuCLIP-seq (CuAAC-Crosslinking and Immunoprecipitation Sequencing), an alternative in situ covalent capture sequencing method which utilizes CuAAC reaction to crosslink RBP-RNA between azido groups of RBPs and ethynyl groups of RNA molecules, followed by streptavidin-mediated enrichment of RNA substrates and high-throughput sequencing. We demonstrate the reliability of CuCLIP-seq by identifying substrate RNAs of several RBPs, including PTBP1, ADAR2, SRSF2, HNRNPA1, and PINX1, especially for capturing low-abundance targets. Additionally, this approach is authenticated by specifically resolving the alternative splicing transcripts targeted by PTBP1 and RNA targets by PINX1. Thus, this technique offers a sensitive and specific approach for detecting RBP substrates with high reproducibility, potential scalability, and wide applicability. Capturing RNA-protein interactions is vital for understanding cellular regulation but remains technically challenging. Here, the authors develop CuCLIP-seq, a sensitive, chemical-crosslinking method that accurately identifies diverse RNA substrates, including low-abundance targets.