Repressive Gene Regulation Synchronizes Development with Cellular Metabolism.

Metabolic conditions affect the developmental tempo of animals. Developmental gene regulatory networks (GRNs) must therefore synchronize their dynamics with a variable timescale. We find that layered repression of genes couples GRN output with variable metabolism. When repressors of transcription or mRNA and protein stability are lost, fewer errors in Drosophila development occur when metabolism is lowered. We demonstrate the universality of this phenomenon by eliminating the entire microRNA family of repressors and find that development to maturity can be largely rescued when metabolism is reduced. Using a mathematical model that replicates GRN dynamics, we find that lowering metabolism suppresses the emergence of developmental errors by curtailing the influence of auxiliary repressors on GRN output. We experimentally show that gene expression dynamics are less affected by loss of repressors when metabolism is reduced. Thus, layered repression provides robustness through error suppression and may provide an evolutionary route to a shorter reproductive cycle.

Energy metabolism modulates the regulatory impact of activators on gene expression.

Gene expression is a regulated process fueled by ATP consumption. Therefore, regulation must be coupled to constraints imposed by the level of energy metabolism. Here, we explore this relationship both theoretically and experimentally. A stylized mathematical model predicts that activators of gene expression have variable impact depending on metabolic rate. Activators become less essential when metabolic rate is reduced and more essential when metabolic rate is enhanced. We find that, in the Drosophila eye, expression dynamics of the yan gene are less affected by loss of EGFR-mediated activation when metabolism is reduced, and the opposite effect is seen when metabolism is enhanced. The effects are also seen at the level of pattern regularity in the adult eye, where loss of EGFR-mediated activation is mitigated by lower metabolism. We propose that gene activation is tuned by energy metabolism to allow for faithful expression dynamics in the face of variable metabolic conditions.

Ratiometric sensing of Pnt and Yan transcription factor levels confers ultrasensitivity to photoreceptor fate transitions in Drosophila.

Cell state transitions are often triggered by large changes in the concentrations of transcription factors and therefore large differences in their stoichiometric ratios. Whether cells can elicit transitions using modest changes in the ratios of co-expressed factors is unclear. Here, we investigate how cells in the Drosophila eye resolve state transitions by quantifying the expression dynamics of the ETS transcription factors Pnt and Yan. Eye progenitor cells maintain a relatively constant ratio of Pnt/Yan protein, despite expressing both proteins with pulsatile dynamics. A rapid and sustained twofold increase in the Pnt/Yan ratio accompanies transitions to photoreceptor fates. Genetic perturbations that modestly disrupt the Pnt/Yan ratio produce fate transition defects consistent with the hypothesis that transitions are normally driven by a twofold shift in the ratio. A biophysical model based on cooperative Yan-DNA binding coupled with non-cooperative Pnt-DNA binding illustrates how twofold ratio changes could generate ultrasensitive changes in target gene transcription to drive fate transitions. Thus, coupling cell state transitions to the Pnt/Yan ratio sensitizes the system to modest fold-changes, conferring robustness and ultrasensitivity to the developmental program.

The characteristics of early-stage research into human genes are substantially different from subsequent research.

Throughout the last 2 decades, several scholars observed that present day research into human genes rarely turns toward genes that had not already been extensively investigated in the past. Guided by hypotheses derived from studies of science and innovation, we present here a literature-wide data-driven meta-analysis to identify the specific scientific and organizational contexts that coincided with early-stage research into human genes throughout the past half century. We demonstrate that early-stage research into human genes differs in team size, citation impact, funding mechanisms, and publication outlet, but that generalized insights derived from studies of science and innovation only partially apply to early-stage research into human genes. Further, we demonstrate that, presently, genome biology accounts for most of the initial early-stage research, while subsequent early-stage research can engage other life sciences fields. We therefore anticipate that the specificity of our findings will enable scientists and policymakers to better promote early-stage research into human genes and increase overall innovation within the life sciences.

A new approach for extracting information from protein dynamics.

Increased ability to predict protein structures is moving research focus towards understanding protein dynamics. A promising approach is to represent protein dynamics through networks and take advantage of well-developed methods from network science. Most studies build protein dynamics networks from correlation measures, an approach that only works under very specific conditions, instead of the more robust inverse approach. Thus, we apply the inverse approach to the dynamics of protein dihedral angles, a system of internal coordinates, to avoid structural alignment. Using the well-characterized adhesion protein, FimH, we show that our method identifies networks that are physically interpretable, robust, and relevant to the allosteric pathway sites. We further use our approach to detect dynamical differences, despite structural similarity, for Siglec-8 in the immune system, and the SARS-CoV-2 spike protein. Our study demonstrates that using the inverse approach to extract a network from protein dynamics yields important biophysical insights.

Impact of COVID-19 on the well-being of children with epilepsy including nodding syndrome in Uganda: A qualitative study.

OBJECTIVE: To investigate the impact of the COVID-19 pandemic and related restrictions on the access and use of health services by children with epilepsy including nodding syndrome in Uganda. METHODS: Four focus group discussions (FGD) with parents/caregivers of children with epilepsy and five in-depth interviews with key informants were conducted between April and May 2021 at Butabika National Mental Referral Hospital and Kitgum General Hospital. RESULTS: COVID-19-related restrictions, including the halting of non-essential services and activities, and suspension of public transport, created several challenges not only for children with epilepsy and their parents/caregivers but also for their healthcare providers. Study participants described extreme transport restrictions that reduced their access to healthcare care services, increased food insecurity and shortage or inability to afford essential medicines as consequences of COVID-19-related restrictions. However, parents/caregivers and healthcare workers adopted several coping strategies for these challenges. Parents/caregivers mentioned taking on casual work to earn an income to buy food, medicines, and other necessities. Healthcare workers intensified outreach services to affected communities. A positive impact of lockdown measures described by some FGD participants was that most family members stayed at home and were able to care for children with epilepsy in turn. CONCLUSIONS: Our study highlights the significant negative impact of the COVID-19 pandemic and related restrictions on access to health services and the general well-being of children with epilepsy. Decentralized epilepsy treatment services and nutritional support could reduce the suffering of children with epilepsy and their families during the ongoing COVID-19 pandemic and similar future emergencies.

Quality of life of persons with epilepsy in Mahenge, an onchocerciasis-endemic area in Tanzania: A cross-sectional study.

OBJECTIVE: This study investigated the quality of life (QoL) of adults with epilepsy living in Mahenge, an onchocerciasis-endemic area in Tanzania with a high prevalence of onchocerciasis-associated epilepsy (OAE). METHODS: Between February and December 2020, persons with epilepsy (PWE) were recruited from four rural villages in Mahenge: Mdindo, Msogezi, Mzelezi, and Sali. For PWE who could not answer the questionnaire due to their mental or physical disability, a family member was asked to answer the questions instead. The Quality of Life in Epilepsy Inventory-31 (QOLIE-31) questionnaire used contained seven domains. The raw domain scores were transformed to 0-100% subscales, with higher scores indicating better QoL. The global QoL was calculated from the subscales using the overall QOLIE-31 score formula. RESULTS: In total, 96 PWE were enrolled in the study with a median age of 28 (range: 18-60) years, of whom 45 (47%) were male. The questionnaires were answered by PWE (54.8%) or one of their family members (45.2%). Most PWE were single (81%), and half never attended school. About two-thirds (65%) of PWE were suspected of having OAE, and a third (31%) had a history of head nodding seizures. Most PWE were treated with phenobarbital (85.4%) and had high treatment adherence (96.9%). Still, the number of seizures per week ranged from 0 to 7, with a median of one. The mean global QOLIE-31 score was 66.9 (range: 38.3-92.1) out of 100.0. Predictors of lower QoL were living in Sali Village and experiencing seizures the week before the interview. In contrast, completing primary school and switching to second-line anti-seizure medication were predictors of higher QoL. CONCLUSION: In order to improve the QoL of PWE in Mahenge, it is vital to optimize anti-seizure medication regimens to decrease the frequency of seizures and to increase the schooling of PWE.

Disability assessment among persons with epilepsy in Mahenge, an onchocerciasis-endemic area in Tanzania: A cross-sectional study.

BACKGROUND: A high prevalence of epilepsy has been observed in the onchocerciasis-endemic focus of Mahenge, Tanzania. This study sought to assess the degree of disability experienced by persons with epilepsy (PWE) in Mahenge and identify associations with sociodemographic and clinical features. METHOD: This cross-sectional study was conducted in Mahenge, Tanzania, between February and July 2020. PWE were recruited from the Mahenge epilepsy clinic and four neighbouring rural villages (Mdindo, Mzogezi, Mzelezi and Sali). Data were collected using the 36-item version of the World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) questionnaire for adults. For children aged 5-17 years, we used the Module on Child Functioning developed by UNICEF and the Washington Group. Questionnaires were administered by trained research assistants. Descriptive statistics were performed, and multivariable analyses (gamma and logistic regressions) were conducted. RESULTS: A total of 321 adults (45.5% males) and 48 children (55.3% males) with epilepsy participated. The overall median WHODAS 2.0 score was 4.8% (IQR: 0.9-18.9). The most affected disability domain was 'participating in the society' (median score: 12.5%, IQR: 0-29.2). Fifteen (31.3%) of the children with epilepsy had a disability in at least one domain of the child functioning module, with the 'accepting change' domain harbouring the highest proportion of disabled children (12.5%). Higher seizure frequency and longer epilepsy duration were associated with more disability. CONCLUSION: PWE in Mahenge experience variable degrees of disability. The affected domains indicate the need for societal rehabilitation of PWE in various community and/or social activities. Peer-support groups were instituted at the study sites to address these needs.

Accessibility to formal education among persons with epilepsy in Mahenge, Tanzania.

BACKGROUND: Epilepsy is estimated to affect 50 million people globally, with 80% living in sub-Saharan Africa (SSA). Children with epilepsy (CWE) in SSA are often socially isolated, and many do not get access to school. This study aimed to explore the barriers hindering accessibility to formal education among CWE in Mahenge, Tanzania. METHODS: The study was conducted in June 2022 in four villages (Mdindo, Msogezi, Mzelezi and Sali) using quantitative and qualitative methods. The quantitative included 203 persons with epilepsy (PWE), while the qualitative involved six focus group discussions and 17 in-depth interviews. Quantitative and qualitative data were analyzed using Stata and Nvivo software, respectively. RESULTS: Of the 203 PWE, 62 (30.5%) had never enrolled in school, while 77 (54.6%) of those enrolled dropped-out before completing it. The perceived barriers to accessing education were categorized as individual barriers (such as frequent seizures, learning difficulties, anti-seizure medication side effects and perceived stigma), Community barriers (such as stigma and discrimination, negative beliefs and misconceptions, relocation to farms and poor socio-economic status), and Institutional barriers (including lack of knowledge about epilepsy among stake-holders, topography and distance to schools). CONCLUSION: There is a high rate of dropouts and non-enrolment of CWE in schools within the Mahenge area. Negative beliefs and low awareness of the community about epilepsy and formal education contribute to this issue. This calls for more advocacy to raise community awareness on epilepsy. The government should enforce an inclusive education policy and provide free and uninterrupted anti-seizure medication for seizure control.

The first step is recognizing there is a problem: a methodology for adjusting for variability in disease severity when estimating clinician performance.

BACKGROUND: Adoption of innovations in the field of medicine is frequently hindered by a failure to recognize the condition targeted by the innovation. This is particularly true in cases where recognition requires integration of patient information from different sources, or where disease presentation can be heterogeneous and the recognition step may be easier for some patients than for others. METHODS: We propose a general data-driven metric for clinician recognition that accounts for the variability in patient disease severity and for institutional standards. As a case study, we evaluate the ventilatory management of 362 patients with acute respiratory distress syndrome (ARDS) at a large academic hospital, because clinician recognition of ARDS has been identified as a major barrier to adoption to evidence-based ventilatory management. We calculate our metric for the 48 critical care physicians caring for these patients and examine the relationships between differences in ARDS recognition performance from overall institutional levels and provider characteristics such as demographics, social network position, and self-reported barriers and opinions. RESULTS: Our metric was found to be robust to patient characteristics previously demonstrated to affect ARDS recognition, such as disease severity and patient height. Training background was the only factor in this study that showed an association with physician recognition. Pulmonary and critical care medicine (PCCM) training was associated with higher recognition (ß = 0.63, 95% confidence interval 0.46-0.80, p < 7 × 10- 5). Non-PCCM physicians recognized ARDS cases less frequently and expressed greater satisfaction with the ability to get the information needed for making an ARDS diagnosis (p < 5 × 10- 4), suggesting that lower performing clinicians may be less aware of institutional barriers. CONCLUSIONS: We present a data-driven metric of clinician disease recognition that accounts for variability in patient disease severity and for institutional standards. Using this metric, we identify two unique physician populations with different intervention needs. One population consistently recognizes ARDS and reports barriers vs one does not and reports fewer barriers.

Conformational stability of the bacterial adhesin, FimH, with an inactivating mutation.

Allostery governing two conformational states is one of the proposed mechanisms for catch-bond behavior in adhesive proteins. In FimH, a catch-bond protein expressed by pathogenic bacteria, separation of two domains disrupts inhibition by the pilin domain. Thus, tensile force can induce a conformational change in the lectin domain, from an inactive state to an active state with high affinity. To better understand allosteric inhibition in two-domain FimH (H2 inactive), we use molecular dynamics simulations to study the lectin domain alone, which has high affinity (HL active), and also the lectin domain stabilized in the low-affinity conformation by an Arg-60-Pro mutation (HL mutant). Because ligand-binding induces an allostery-like conformational change in HL mutant, this more experimentally tractable version has been proposed as a "minimal model" for FimH. We find that HL mutant has larger backbone fluctuations than both H2 inactive and HL active, at the binding pocket and allosteric interdomain region. We use an internal coordinate system of dihedral angles to identify protein regions with differences in backbone and side chain dynamics beyond the putative allosteric pathway sites. By characterizing HL mutant dynamics for the first time, we provide additional insight into the transmission of allosteric information across the lectin domain and build upon structural and thermodynamic data in the literature to further support the use of HL mutant as a "minimal model." Understanding how to alter protein dynamics to prevent the allosteric conformational change may guide drug development to prevent infection by blocking FimH adhesion.

Large-scale investigation of the reasons why potentially important genes are ignored.

Biomedical research has been previously reported to primarily focus on a minority of all known genes. Here, we demonstrate that these differences in attention can be explained, to a large extent, exclusively from a small set of identifiable chemical, physical, and biological properties of genes. Together with knowledge about homologous genes from model organisms, these features allow us to accurately predict the number of publications on individual human genes, the year of their first report, the levels of funding awarded by the National Institutes of Health (NIH), and the development of drugs against disease-associated genes. By explicitly identifying the reasons for gene-specific bias and performing a meta-analysis of existing computational and experimental knowledge bases, we describe gene-specific strategies for the identification of important but hitherto ignored genes that can open novel directions for future investigation.

Reply to "Far away from the lamppost".

In this Formal Comment, the authors of the recent publication "Large-scale investigation of the reasons why potentially important genes are ignored" maintain that it can be read as an opportunity to explore the unknown.

Fly-QMA: Automated analysis of mosaic imaginal discs in Drosophila.

Mosaic analysis provides a means to probe developmental processes in situ by generating loss-of-function mutants within otherwise wildtype tissues. Combining these techniques with quantitative microscopy enables researchers to rigorously compare RNA or protein expression across the resultant clones. However, visual inspection of mosaic tissues remains common in the literature because quantification demands considerable labor and computational expertise. Practitioners must segment cell membranes or cell nuclei from a tissue and annotate the clones before their data are suitable for analysis. Here, we introduce Fly-QMA, a computational framework that automates each of these tasks for confocal microscopy images of Drosophila imaginal discs. The framework includes an unsupervised annotation algorithm that incorporates spatial context to inform the genetic identity of each cell. We use a combination of real and synthetic validation data to survey the performance of the annotation algorithm across a broad range of conditions. By contributing our framework to the open-source software ecosystem, we aim to contribute to the current move toward automated quantitative analysis among developmental biologists.

Multidimensional Assessment of the Host Response in Mechanically Ventilated Patients with Suspected Pneumonia.

Rationale: The identification of informative elements of the host response to infection may improve the diagnosis and management of bacterial pneumonia. Objectives: To determine whether the absence of alveolar neutrophilia can exclude bacterial pneumonia in critically ill patients with suspected infection and to test whether signatures of bacterial pneumonia can be identified in the alveolar macrophage transcriptome. Methods: We determined the test characteristics of alveolar neutrophilia for the diagnosis of bacterial pneumonia in three cohorts of mechanically ventilated patients. In one cohort, we also isolated macrophages from alveolar lavage fluid and used the transcriptome to identify signatures of bacterial pneumonia. Finally, we developed a humanized mouse model of Pseudomonas aeruginosa pneumonia to determine if pathogen-specific signatures can be identified in human alveolar macrophages. Measurements and Main Results: An alveolar neutrophil percentage less than 50% had a negative predictive value of greater than 90% for bacterial pneumonia in both the retrospective (n = 851) and validation cohorts (n = 76 and n = 79). A transcriptional signature of bacterial pneumonia was present in both resident and recruited macrophages. Gene signatures from both cell types identified patients with bacterial pneumonia with test characteristics similar to alveolar neutrophilia. Conclusions: The absence of alveolar neutrophilia has a high negative predictive value for bacterial pneumonia in critically ill patients with suspected infection. Macrophages can be isolated from alveolar lavage fluid obtained during routine care and used for RNA-Seq analysis. This novel approach may facilitate a longitudinal and multidimensional assessment of the host response to bacterial pneumonia.

Single-Cell Transcriptomic Analysis of Human Lung Provides Insights into the Pathobiology of Pulmonary Fibrosis.

Rationale: The contributions of diverse cell populations in the human lung to pulmonary fibrosis pathogenesis are poorly understood. Single-cell RNA sequencing can reveal changes within individual cell populations during pulmonary fibrosis that are important for disease pathogenesis. Objectives: To determine whether single-cell RNA sequencing can reveal disease-related heterogeneity within alveolar macrophages, epithelial cells, or other cell types in lung tissue from subjects with pulmonary fibrosis compared with control subjects. Methods: We performed single-cell RNA sequencing on lung tissue obtained from eight transplant donors and eight recipients with pulmonary fibrosis and on one bronchoscopic cryobiospy sample from a patient with idiopathic pulmonary fibrosis. We validated these data using in situ RNA hybridization, immunohistochemistry, and bulk RNA-sequencing on flow-sorted cells from 22 additional subjects. Measurements and Main Results: We identified a distinct, novel population of profibrotic alveolar macrophages exclusively in patients with fibrosis. Within epithelial cells, the expression of genes involved in Wnt secretion and response was restricted to nonoverlapping cells. We identified rare cell populations including airway stem cells and senescent cells emerging during pulmonary fibrosis. We developed a web-based tool to explore these data. Conclusions: We generated a single-cell atlas of pulmonary fibrosis. Using this atlas, we demonstrated heterogeneity within alveolar macrophages and epithelial cells from subjects with pulmonary fibrosis. These results support the feasibility of discovery-based approaches using next-generation sequencing technologies to identify signaling pathways for targeting in the development of personalized therapies for patients with pulmonary fibrosis.

Within-Gene Shine-Dalgarno Sequences Are Not Selected for Function.

The Shine-Dalgarno (SD) sequence motif facilitates translation initiation and is frequently found upstream of bacterial start codons. However, thousands of instances of this motif occur throughout the middle of protein coding genes in a typical bacterial genome. Here, we use comparative evolutionary analysis to test whether SD sequences located within genes are functionally constrained. We measure the conservation of SD sequences across Enterobacteriales, and find that they are significantly less conserved than expected. Further, the strongest SD sequences are the least conserved whereas we find evidence of conservation for the weakest possible SD sequences given amino acid constraints. Our findings indicate that most SD sequences within genes are likely to be deleterious and removed via selection. To illustrate the origin of these deleterious costs, we show that ATG start codons are significantly depleted downstream of SD sequences within genes, highlighting the constraint that these sequences impose on the surrounding nucleotides to minimize the potential for erroneous translation initiation.

Diversity of Translation Initiation Mechanisms across Bacterial Species Is Driven by Environmental Conditions and Growth Demands.

The Shine-Dalgarno (SD) sequence motif is frequently found upstream of protein coding genes and is thought to be the dominant mechanism of translation initiation used by bacteria. Experimental studies have shown that the SD sequence facilitates start codon recognition and enhances translation initiation by directly interacting with the highly conserved anti-SD sequence on the 30S ribosomal subunit. However, the proportion of SD-led genes within a genome varies across species and the factors governing this variation in translation initiation mechanisms remain largely unknown. Here, we conduct a phylogenetically informed analysis and find that species capable of rapid growth contain a higher proportion of SD-led genes throughout their genomes. We show that SD sequence utilization covaries with a suite of genomic features that are important for efficient translation initiation and elongation. In addition to these endogenous genomic factors, we further show that exogenous environmental factors may influence the evolution of translation initiation mechanisms by finding that thermophilic species contain significantly more SD-led genes than mesophiles. Our results demonstrate that variation in translation initiation mechanisms across bacterial species is predictable and is a consequence of differential life-history strategies related to maximum growth rate and environmental-specific constraints.

Differences in Collaboration Patterns across Discipline, Career Stage, and Gender.

Collaboration plays an increasingly important role in promoting research productivity and impact. What remains unclear is whether female and male researchers in science, technology, engineering, and mathematical (STEM) disciplines differ in their collaboration propensity. Here, we report on an empirical analysis of the complete publication records of 3,980 faculty members in six STEM disciplines at select U.S. research universities. We find that female faculty have significantly fewer distinct co-authors over their careers than males, but that this difference can be fully accounted for by females' lower publication rate and shorter career lengths. Next, we find that female scientists have a lower probability of repeating previous co-authors than males, an intriguing result because prior research shows that teams involving new collaborations produce work with higher impact. Finally, we find evidence for gender segregation in some sub-disciplines in molecular biology, in particular in genomics where we find female faculty to be clearly under-represented.