Journal of Microbiology & Biology Education

ObjectivesEffective communication about genetics concepts is essential for collaborative anthropological genetics research. However, communication can be challenging because many ideas are abstract and may be especially unfamiliar to communities with limited access to formal education. Indeed, there are no widely adopted models for communicating such information, nor a clear understanding of the social factors that may shape participant engagement. Here, we conducted a qualitative and quantitative, community-driven study to understand how illustrations can be useful to support concept sharing with two Indigenous groups--the Orang Asli of Peninsular Malaysia and the Turkana of Kenya. MethodsWe used a two phase approach to create and evaluate how illustrations can bolster communication about genetics concepts. First, we created images illustrating answers to frequently asked questions about genetics, iteratively updating the illustrations based on participant feedback. Second, we conducted 92 interviews to evaluate the finalized illustrations effectiveness. Finally, we analyzed the interview data using thematic analyses, multivariable modeling, and multiple correspondence analyses to identify patterns in participant understanding and feedback, including age, sex, market integration, and schooling. ResultsParticipants reported high interest in genetics research (92%) and broadly positive perceptions of the illustrations. Familiar, locally-grounded imagery was preferred and associated with greater perceived clarity, while more technical illustrations were more frequently reported as confusing. Quantitative analyses showed strong internal consistency across measures of engagement and understanding, with modest variation by degree of market-integration, schooling, and sex. DiscussionOur findings demonstrate that community-specific visualizations, co-developed through iterative feedback, can effectively support engagement with genetics research in participant communities.

The transition to higher education is characterized by increased academic demands and psychosocial stress, which may negatively affect cognitive functioning and student well-being. Executive functions (working memory, inhibitory control, and cognitive flexibility) are critical for academic adaptation and can be enhanced through structured interventions. Physical exercise, mind-body practices, and cognitive training have demonstrated potential benefits for executive functioning and stress reduction; however, few randomized controlled trials have directly compared interventions with different physical and cognitive demands in university students, particularly in Latin America. In addition, most studies have relied on self-report measures and physiological stress biomarkers such as salivary cortisol. This protocol describes a three-arm, parallel-group randomized controlled trial designed to evaluate the effects of a 12-week intervention on executive functions and stress in first-year university students. The study will recruit 120 first-year health-science students aged 18-25 years. Participants will be randomly assigned (1:1:1), using block randomization stratified by sex, to one of three interventions delivered twice weekly (24 sessions of 60 minutes): (1) moderate-to-vigorous motor-cognitive dual-task exercise (DT); (2) low-to-moderate intensity Tai Chi (TC); or (3) supervised digital cognitive stimulation (CS) using structured graphomotor tasks. Primary outcomes include executive functions assessed through standardized neuropsychological measures. Secondary outcomes include stress will be evaluated using the Academic Stress Inventory, Depression Anxiety Stress Scales and salivary cortisol collected in the morning using passive drool and analyzed by competitive ELISA.Other outcomes include physical activity levels, anthropometric and body composition measures, and handgrip strength. Data will be analyzed following an intention-to-treat approach using repeated-measures models, with multiple imputation for missing data. The study has received institutional ethics and biosafety approval. Trial registration: ClinicalTrials.gov Identifier: NCT07443904.

PurposeThis study examined the association between traditional physical practice participation and vision-related quality of life among junior secondary school students and tested the mediating roles of exercise self-efficacy and visual function anomalies within a serial mediation framework. MethodsA four-wave time-lagged survey was conducted among 1,579 students in Grades 7-9 from schools implementing traditional physical practice activities. Variables were assessed at two-week intervals. Mediation effects were tested using the bias-corrected percentile bootstrap method with 5,000 resamples. ResultsThe total effect of traditional physical practice participation on vision-related quality of life was significant ({beta} = 0.591, p < .001). After including the mediators, the direct effect remained significant ({beta} = 0.404, 95% CI [0.348, 0.457]), accounting for 68.36% of the total effect. The total indirect effect was significant ({beta} = 0.187, 95% CI [0.160, 0.218]), representing 31.64% of the total effect. The indirect effect via exercise self-efficacy was significant ({beta} = 0.088, 95% CI [0.068, 0.112], 14.89%), as was the indirect effect via visual function anomalies ({beta} = 0.065, 95% CI [0.048, 0.086], 11.00%). The serial mediation pathway through exercise self-efficacy and visual function anomalies was also significant ({beta} = 0.034, 95% CI [0.025, 0.045], 5.75%). All confidence intervals excluded zero, supporting partial mediation. ConclusionTraditional physical practice participation was associated with vision-related quality of life both directly and indirectly through exercise self-efficacy and visual function anomalies, including a significant serial mediation pathway. The findings highlight the combined psychological and functional mechanisms underlying adolescents vision-related quality of life.

Generative artificial intelligence (genAI) tools are increasingly used by prospective higher education (HE) applicants seeking guidance on university and programme selection. Despite rapidly expanding use, little is known about how genAI systems may introduce or amplify bias in undergraduate admissions decision-making. Here, we systematically examined patterns of bias across three widely used genAI chatbots (ChatGPT, Copilot, Gemini) using neuroscience as a representative UK undergraduate programme. We constructed 216 prompts that varied by applicant characteristics (e.g. gender, study type, academic attainment). Each prompt was submitted to all three chatbots, generating 648 responses and 3240 individual programme recommendations. Output responses underwent text analysis (e.g. n-grams, gender-coded language), and national HE markers of esteem (REF21, TEF23, NSS24) were analysed. Applicant grades and priorities produced the strongest effects on genAI outputs. Higher-grade applicants and those prioritising research received significantly more masculine-coded language, independent of applicant gender. N-gram patterns also diverged: high-grade prompts more frequently elicited terms relating to excellence and research intensity, whereas lower-grade prompts produced greater emphasis on widening access. Recommendations were systematically skewed, with higher grades, private schooling, and research-focused priorities increasing the likelihood of recommending elite institutions and programmes with higher entry requirements. Critically, the gender-coded language of outputs predicted institutional characteristics: masculine-coded responses were associated with recommendations featuring higher entry thresholds and stronger research performance, while feminine-coded responses favoured institutions with higher student satisfaction. These findings reveal clear, systematic biases in how genAI guides prospective HE applicants. Such biases risk reinforcing existing educational and socioeconomic inequalities, underscoring the need for transparency, regulation, and oversight in the use of genAI within HE decision-making. HighlightsO_LIGenAI is widely used by HE applicants despite little study of its biases. C_LIO_LI216 prompts across 3 chatbots generated 3240 programme suggestions. C_LIO_LIGrades and priorities drove major shifts in language and recommendations. C_LIO_LIGender-coded wording mapped onto research strength and entry standards. C_LIO_LIGenAI biases may reinforce inequalities in HE admissions decision-making. C_LI

This dataset arises from a multilingual survey of AI use among participants and community members in the DBCLS BioHackathon 2025 in Japan. The questionnaire, offered in English, Japanese, and Thai, asked about how often respondents use AI tools, what they use them for, obstacles they encounter, institutional support, satisfaction, and concerns. Additional items captured role, institution type, work country, and other demographics, totaling 105 responses. The dataset includes both raw anonymized responses and a cleaned, standardized English-only version suitable for quantitative analysis, along with the full questionnaire, a data dictionary for cleaned dataset, and a translation lookup table. Free-text answers were screened and redacted to remove URLs, names, and other potentially identifiable information. Together, these materials provide a community-level view of AI practice in genomics, bioinformatics, software development, and related areas, and can support work on AI adoption, policy, and methods for analyzing survey data on AI use in science.

If youve ever complained about a species name thats a mouthful--say, the soldier fly Parastratiosphecomyia stratiosphecomyioides or the myxobacterium Myxococcus llanfairpwllgwyngyllgogerychwyrndrobwllllantysiliogogogochensis--youre in very good company. But could the readability of binomial scientific names cause more than complaints? Could it influence how much species are studied and talked about? We examined a random sample of 3,019 species names spanning 29 phyla/divisions. We tested whether name length and reading difficulty are associated with species representation in the scientific literature (measured via literature mentions) and their visibility to the public (measured via Wikipedia pageviews). Both species name traits showed significant negative relationships with literature mentions and Wikipedia reads. Increasing name length from 10 to 30 characters is associated with a 66% decrease in expected mentions and a 65% decrease in Wikipedia reads, while shifting from the most to the least readable name in the dataset corresponds to 53% and 76% decreases. These patterns are consistent with something familiar: the fickleness of human attention, responding to features of the world that are far from rational. While creativity in naming is a cherished part of taxonomy, a touch of orthographic restraint may ultimately benefit both science and the species themselves--especially among understudied uncharismatic taxa.

We report the discovery and structure of a previously unknown ~1 MDa hollow protein assembly, identified during a survey of ciliary complexes from the ciliate Tetrahymena thermophila. By combining mass spectrometry, structure prediction, and cryo-electron microscopy, we define a homotetrameric cage-like complex with a distinctive elliptical architecture and a large internal cavity. A sequence survey revealed several thousand homologs spanning diverse unicellular eukaryotes--including green algae, fungi, amoebozoans, choanoflagellates, and SAR lineages--as well as predominantly gram-negative bacteria, indicating an ancient evolutionary origin and arguing against a eukaryote-specific function. We determined a near-atomic resolution structure of the complex from the slime mold Dictyostelium discoideum, demonstrating conservation of overall architecture and cavity despite low sequence identity. Together, these results establish the CAGE complex (Conserved Assembly in Gram-negative bacteria and Eukaryotes) as a new class of large protein cage broadly distributed across the tree of life. While its biological function remains unknown, its size, architecture, and conservation suggest possible roles in transport or protein/RNA homeostasis.

In living systems across developmental and cancer biology, populations of cells on surfaces organize themselves into aggregates that mediate function and disease. Recent experimental studies have identified that such aggregates can have emergent fluid-like properties such as surface tension, yet the physical origin of these properties is not clear. Here, we develop a minimal cell-based model in which cell-cell and cell-substrate interactions are governed by active intermittent attachments. We explain the transition of cells from a dilute population to a dense aggregate, and quantify the emergent material properties underpinning this transition. We use our model to interpret experiments on dewetting of aggregates of MDA-MDB-231 cancer cells and shape fluctuations of surface-associated OVCAR3 cell aggregates. Finally, we show how spatial heterogeneity in attachments governs collective chemotaxis of cell aggregates. Together, these results reveal how active intermittent attachments generate cell aggregates with emergent material properties, with broad implications for development and cancer.

Introduction: Following a large chikungunya outbreak during 2006 to 2008, Sri Lanka did not report any outbreaks for a 16 year period until end of 2008, possibly due to population immunity. Therefore, understanding baseline immunity prior to outbreaks is crucial to inform implementation of vaccine strategies. Methods: We assessed the age stratified seroprevalence for chikungunya in an urban (n=816) and a semi urban (n=380) community in Colombo, Sri Lanka, from September to November 2024, prior to the commencement of the large chikungunya outbreak, in December 2024. Sociodemographic, socioeconomic and clinical data were collected and chikungunya specific IgG measured in serum samples. Results: Of 1196 participants, 410 (34.3%) were chikungunya IgG seropositive. Seroprevalence was significantly higher in urban populations compared with semi urban populations (39.6% vs 22.9%; p<0.001) and increased significantly with age in urban areas but not in semi-urban areas. Living in an urban area was the strongest independent risk factor of chikungunya seropositivity (aOR 7.48, 95% CI 4.05 to 13.81; p<0.001), consistent with the higher population density, poor housing conditions and overcrowding observed in that setting. The use of mosquito nets was independently associated with reduced risk of seropositivity (aOR 0.50, 95% CI 0.27 to 0.93; p=0.029). Almost no individuals aged <16 years had evidence of prior infection (0.55%), indicating minimal transmission in the preceding 16 years. In the urban cohort, seropositivity was significantly associated with diabetes, central obesity, overweight, and hypertension. Conclusions: There appears to have been minimal chikungunya transmission in the 16 years preceding the 2024 outbreak, with a large population susceptible to chikungunya. Higher seroprevalence in urban populations highlights the role of population density, overcrowding, and housing conditions as key drivers of transmission.

Unlike the stable transcription of plant genes with CG gene body methylation alone, genes with methylation in TE-like CHG and CG contexts are poorly transcribed and often missanotated. In contrast, here we describe a set of TE-like methylated genes that are maternally demethylated and expressed toward the extreme high end of the spectrum in endosperm. They are enriched for short, secreted proteins, and about a third encode zeins, the major seed storage proteins of maize. Consistent with their dynamic expression in endosperm, they acquire either activating or repressive gene regulatory modifications when demethylated but are heterochromatic when methylated in other tissues. The majority are expressed both maternally and paternally, but a subset whose methylation/demethylation extends upstream of gene bodies into promoters are strongly imprinted. These and other data indicate that TE-like methylation and associated heterochromatin can be a signature of broad silencing but exceptionally high and specific gene expression in either pollen or endosperm.

Perceiving the direction of observed actions is critical for interpreting intentions and guiding social interaction. While direction selectivity has been extensively studied with simple stimuli such as dots, gratings, or point-light displays (PLDs), little is known about how the brain encodes direction in naturalistic, repetitive actions that are seen frequently in daily life. The present fMRI study investigated direction-selective representations during observation of complex actions performed along three bidirectional dimensions (left-right, up-down, front-back) within a 96-video stimulus set. The brain activity was analyzed using multivariate pattern analysis (MVPA) and multiple regression representational similarity analysis (RSA). MVPA revealed above-chance classification of action direction across occipital, parietal, and motor cortices, with the highest decoding in occipital, primary motor, and somatosensory regions. Crucially, RSA demonstrated that when accounting for low-level and motor features, direction information was still represented in early visual cortex, occipito-temporal areas, parietal regions, and motor-related regions. These findings indicate that action direction is represented across multiple levels of the action observation network (AON), extending from early sensory regions to higher-order parietal and frontal cortices. By using naturalistic, repetitive action videos, this study provides new evidence that the coding of action direction in the human brain is broadly distributed, reflecting the complexity of perceiving actions in everyday life. These findings suggest that direction selectivity is a core feature of the action observation network, linking basic motion processing with higher-level action understanding.

Mutations in human LIS1 cause lissencephaly, a severe developmental brain malformation. Although most stud-ies focus on development, LIS1 is also expressed in adult mouse tissues. We previously induced LIS1 knockout (iKO) in adult mice using a Cre-Lox approach with an actin promoter driving CreERT2 expression. This proved to be rapidly lethal, with evidence pointing toward nervous system dysfunction. CreERT2 activity was observed in astrocytes, brainstem and spinal motor neurons, and axons and Schwann cells in the sciatic and phrenic nerves, suggesting dysfunctional cardiorespiratory and motor circuits. However, it is unclear how LIS1 knockout in these different cell types contributes to the lethal phenotype. We now report that LIS1 depletion from astro-cytes is not lethal to mice (male or female), although glial fibrillary protein (GFAP) expression is increased in all LIS1-depleted astrocytes. In contrast, LIS1 depletion from projection neurons causes motor deficits and rapid lethality in both males and females. This is accompanied by progressive, widespread axonal degeneration along the entire length of both motor and sensory axons. Interestingly, sensory neurons harvested from iKO mice ini-tially extend axons in culture but soon develop axonal swellings and fragmentation, indicating axonal degenera-tion. LIS1 is a prominent regulator of cytoplasmic dynein 1 (dynein, hereafter), a microtubule motor whose dis-ruption can cause both cortical malformations and later-onset neurodegenerative diseases, such as Charcot-Marie-Tooth disease. Our results raise the possibility that LIS1 depletion, through disruption of dynein function in mature axons, may lead to Wallerian-like axon degeneration without traumatic nerve injury.

In brain-heart interactions, several pathways have been proposed to mediate feedback loops between systems. Among these, cerebrovascular dynamics operate at their interface. However, how cardiovascular control, ventilation mechanisms, and cerebral autoregulation interact is not well characterized, especially in ageing and post-stroke conditions, where perfusion can be compromised. In a cohort of 57 elderly participants, including 30 stroke survivors, we investigated the relationship between cardiac sympathetic activity and both, cerebral blood flow regulation and ventilatory status. Sympathetic reflexes, assessed via cardiac sympathetic index (CSI) during sit-to-stand transitions, were preserved across all participants, with marginal group differences between stroke and non-stroke populations. However, among individuals with constrained ventilation, indexed by reduced end-tidal CO2 at baseline, we identified a more elevated CSI following postural change, scaling with the degree of CO2 dysregulation. Furthermore, transcranial Doppler measurements revealed exaggerated changes in mean flow velocity (MFV) within the right middle cerebral artery in most participants. These MFV shifts significantly correlated with the magnitude of cardiac sympathetic change under orthostatic stress, suggesting that CSI can capture maladaptive cerebrovascular responses. Together, these findings highlight a distinct cardiac-cerebrovascular crosstalk in elderly individuals, revealing patterns consistent with compensatory or maladaptive sympathetic overactivation under conditions of impaired cerebrovascular control.

Rhomboid proteases play fundamental roles in human biology and disease by cleaving substrate transmembrane domains. However, the absence of structural data and the inability to identify substrates for orphan human rhomboids limit mechanistic understanding. Lateral gating is considered the primary route by which transmembrane substrates access the rhomboid active site, although this has been demonstrated directly only for the bacterial rhomboid GlpG. To address this, we characterised the structures, conformational ensembles, and energy landscapes of human rhomboid proteases using AI-based structural models and molecular dynamics simulations, benchmarked by simulations seeded with GlpG crystal structures and models. We find that while some human rhomboids readily transition to open conformations compatible with transmembrane substrate access, orphan rhomboids possess unusually narrow lateral gates that require substantially higher energy to open. Our results reveal unexpected diversity in substrate engagement mechanisms among human rhomboids, and provide a rationale for the orphan status of recently evolved family members.

Genotype-phenotype databases are essential for variant interpretation and disease gene discovery. Genetic variation differs among human populations, mainly in allele frequencies and haplotype patterns shaped by ancestry and demographic history. Population-specific genotypes can influence traits and disease risk; this makes population specific characterization important. Most existing resources focus on the characterization of a population's genetic background, but do not represent the resulting phenotypes. We have developed PAVS (Phenotype-Associated Variants in Saudi Arabia), a curated, publicly accessible database that integrates 5,132 Saudi clinical cases from four Saudi cohorts and 522 cases from analysis of a mixed-population cohort, together with 1,856 cases from the Deciphering Developmental Disorders study (DDD) and 9,588 literature phenopackets. Each case record describes patient-level phenotypes, encoded with the Human Phenotype Ontology (HPO), and links them to genomic variants, gene identifiers, zygosity, pathogenicity classifications, and disease diagnoses mapped to standardized disease terminologies. The data is represented in Phenopackets format and as a knowledge graph in RDF. Additionally, a web interface provides phenotype-based similarity search, gene and variant browsers, and an HPO hierarchy explorer. We evaluate the utility of the phenotype annotations for gene prioritization using semantic similarity. While there are clear differences to global literature-curated databases, phenotypes in PAVS can successfully rank the correct gene at high rank (ROCAUC: 0.89). PAVS addresses a gap in population-specific genotype-phenotype resources and provides a benchmark for phenotype-driven variant prioritization in under-represented populations.

Mitochondrial genomes retain only a tiny number of genes from their bacterial progenitors, including key components of protein translation machinery. The set of mitochondrially encoded tRNAs and ribosomal subunits is highly variable across angiosperms, with many examples of mitochondrial gene loss, replacement, and/or transfer to the nucleus. This dynamic history suggests large-scale remodeling of mitochondrial translation machinery in some lineages, but such conclusions are largely inferred from genomic sequence and protein targeting predictions. Here, we use proteomic (LC-MS/MS) analysis of purified mitochondria and chloroplasts from angiosperm species with major differences in mitochondrial gene content (Arabidopsis thaliana and Silene conica). Our analysis largely confirms the current understanding of subcellular localization for nuclear-encoded proteins involved in tRNA metabolism and ribosome function in A. thaliana, although some aminoacyl-tRNA synthetases (aaRSs) may have more specialized subcellular roles than previously thought. In contrast, S. conica has undergone extensive mitochondrial gene loss and numerous associated changes in the composition of its mitochondrial proteome, including apparent retargeting of aaRSs, replacement of ribosomal subunits, and loss of the glutamine amidotransferase (GatCAB) complex. Overall, this analysis illustrates how the complex network of molecular interactions necessary for mitochondrial translation are perturbed by gene loss, transfer, and replacement.

Bacteriophages are not only the most ubiquitous biological entity on earth, they also display remarkable genetic diversity across and within populations. While macrodiversity has been extensively studied, the drivers of microdiversity (intraspecies genetic diversity) remain poorly understood, particularly in relation to phage lifestyle. The distinguishing ability of temperate phages to integrate themselves into the host genome has an unknown influence on the microdiversity present. This difference in microdiversity could impact the adaptability of phages to (a)biotic factors. To identify a possible association between microdiversity and lifestyle, we analysed 12 existing viromics datasets focusing on soil bacteriophages, including 41 412 viral genomes in total. We found that phages predicted to be temperate consistently exhibit significantly higher microdiversity than their virulent counterparts in eight of 12 datasets, whereas the remaining four datasets did not show a significant trend. The detected pattern holds across multiple quality thresholds and lifestyle prediction methods. These findings suggest that lysogeny may promote or preserve genetic variation within phage populations, with potential implications for phage-host coevolution and environmental adaptability.

Understanding how spinal circuits shape motor neuron behavior during muscle contractions remains a major challenge. Here, we combined large-scale motor unit recordings with simulation-based inference to generate probabilistic estimates of homonymous and heteronymous recurrent inhibition, a key spinal circuit that has remained largely inaccessible during natural voluntary contractions. We constructed synchronization cross-histograms from motor neuron spike trains and extracted features representative of recurrent inhibition. Because these features are also influenced by higher-frequency components of common synaptic input, we developed a simulation-based inference framework to disentangle these effects. Following validation, we applied this framework to experimental data from six muscles at two contraction intensities, revealing previously uncharacterized muscle- and intensity-dependent patterns: recurrent inhibition decreased with contraction intensity in most muscles but increased in the vastus lateralis and medialis. The pipeline is openly available and designed for reuse on comparable datasets and for adaptation to diverse experimental contexts, including other spinal circuits.

Purpose: DNM1-related disorder is a rare developmental and epileptic encephalopathy. The current understanding of the clinical spectrum is based on sparse patient descriptions. Here, we compile the largest DNM1 cohort to date, to characterize the genotypic and phenotypic landscape of the disorder. Methods: Phenotypic data was manually curated from 95 individuals from multiple sources and harmonized using the Human Phenotype Ontology framework. Results: Disease-causing variants in DNM1 cluster in mutational hotspots within the gene, which achieve Strong and Moderate evidence for pathogenicity based on ACMG guidelines. The overall DNM1 phenotype was homogeneous compared to other genetic epilepsy conditions: SCN2A, SCN8A, STXBP1, and SYNGAP1. The p.R237W (n=15) variant was associated with bilateral tonic-clonic seizures, infantile spasms, and dystonia. The p.I398_R399insCR (n=14) variant was associated with severe hypotonia, profound global delay, and cortical visual impairment. Five individuals with homozygous loss-of-function variants were clinically similar to dominant-negative DNM1-related disorder, but microcephaly and brain MRI abnormalities were more common in this group. Conclusion: A harmonized cohort of individuals with DNM1-related disorder was analyzed to define mutational hotspots and reveal novel genotype-phenotype correlations. Due to the homogeneous phenotype, disease mechanism, and high proportion of recurrent variants, DNM1 represents an attractive target for targeted therapy development.

The evolution of plant resistance naturally occurs in complex, multifaceted environments that consist of multiple simultaneous stressors. Understanding how shifting environmental contexts may shape resistance evolution requires empirical studies that consider the combined effects of interacting stressors on fitness and selection. Here, we examined how exposure to an insecticide impacts the evolution of resistance to the herbicide glyphosate in Ipomoea purpurea (common morning glory). Through a factorial field experiment, we manipulated glyphosate and an insecticide to estimate selection on glyphosate and herbivory resistance. We found that glyphosate acted as the primary agent of selection, favoring higher levels of glyphosate resistance. In the presence of glyphosate alone, positive correlational selection favored a combination of higher glyphosate and herbivory resistance, supporting prior work that suggested these traits may be linked. Importantly, insecticide exposure modified both glyphosate resistance and the strength of selection acting upon the trait by increasing resistance and weakening selection. Together, our results indicate that the evolution of herbicide resistance is context-dependent and that secondary stressors like insecticide can alter the evolutionary trajectories of plant defense.