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ABSTRACT Acute respiratory distress syndrome (ARDS) is an often fatal critical illness where lung epithelial injury leads to intrapulmonary fluid accumulation. ARDS became widespread during the COVID-19 pandemic, motivating a renewed effort to understand the complex etiology of this disease. Rigorous prior work has implicated lung endothelial and epithelial injury in response to an insult such as bacterial infection; however, the impact of microorganisms found in other organs on ARDS remains unclear. Here, we use a combination of gnotobiotic mice, cell culture experiments, and re-analyses of a large metabolomics dataset from ARDS patients to reveal that gut bacteria impact lung cellular respiration by releasing metabolites that alter mitochondrial activity in lung epithelium. Colonization of germ-free mice with a complex gut microbiota stimulated lung mitochondrial gene expression. A single human gut bacterial species,Bifidobacterium adolescentis,was sufficient to replicate this effect, leading to a significant increase in mitochondrial membrane potential in lung epithelial cells. We then used genome sequencing and mass spectrometry to confirm thatB. adolescentisproducesL-lactate, which was sufficient to increase mitochondrial activity in lung epithelial cells. Finally, we found that serum lactate was significantly associated with disease severity in patients with ARDS from the Early Assessment of Renal and Lung Injury (EARLI) cohort. Together, these results emphasize the importance of more broadly characterizing the microbial etiology of ARDS and other lung diseases given the ability of gut bacterial metabolites to remotely control lung cellular respiration. Our discovery of a single bacteria-metabolite pair provides aproof-of-conceptfor systematically testing other microbial metabolites and a mechanistic biomarker that could be pursued in future clinical studies. Furthermore, our work adds to the growing literature linking the microbiome to mitochondrial function, raising intriguing questions as to the bidirectional communication between our endo- and ecto-symbionts. 

Background:The Glycemia Risk Index (GRI) was developed in adults with diabetes and is a validated metric of quality of glycemia. Little is known about the relationship between GRI and type 1 diabetes (T1D) self-management habits, a validated assessment of youths’ engagement in habits associated with glycemic outcomes. Method:We retrospectively examined the relationship between GRI and T1D self-management habits in youth with T1D who received care from a Midwest pediatric diabetes clinic network. The GRI was calculated using seven days of continuous glucose monitor (CGM) data, and T1D self-management habits were assessed ±seven days from the GRI score. A mixed-effects Poisson regression model was used to evaluate the total number of habits youth engaged in with GRI, glycated hemoglobin A1c (HbA1c), age, race, ethnicity, and insurance type as fixed effects and participant ID as a random effect to account for multiple clinic visits per individual. Results:The cohort included 1182 youth aged 2.5 to 18.0 years (mean = 13.8, SD = 3.5) comprising 50.8% male, 84.6% non-Hispanic White, and 64.8% commercial insurance users across a total of 6029 clinic visits. Glycemia Risk Index scores decreased as total number of habits performed increased, suggesting youth who performed more self-management habits achieved a higher quality of glycemia. Conclusions:In youth using CGMs, GRI may serve as an easily obtainable metric to help identify youth with above target glycemia, and engagement/disengagement in the T1D self-management habits may inform clinicians with suitable interventions for improving glycemic outcomes. 

Although child participation is required for successful Type 1 Diabetes (T1D) management, it is challenging because the child’s young age and immaturity make it difficult to perform self-care. Thus, parental caregivers are expected to be heavily involved in their child’s everyday illness management. Our study aims to investigate how children and parents collaborate to manage T1D and examine how the children become more independent in their self-management through the support of their parents. Through semi-structured interviews with children with T1D and their parents (N=41), our study showed that children’s knowledge of illness management and motivation for self-care were crucial for their transition towards independence. Based on these two factors, we identified four types of children’s collaboration (i.e., dependent, resistant, eager, and independent) and parents’ strategies for supporting their children’s independence. We suggest design implications for technologies to support collaborative care by improving children’s transition to independent illness management. 

Children with Type 1 Diabetes (T1D) face many challenges with keeping their blood glucose levels within a healthy range because they cannot manage their illness by themselves. To prevent children’s blood glucose from becoming too high or too low, parents apply different strategies to avoid risky situations. To understand how parents of children with T1D manage these risks, we conducted semi-structured interviews with children with T1D (ages 6-12) and their parents (N=41). We identified four types of strategies used by parents (i.e., educated guessing game, contingency planning, experimentation, and reaching out for help) that can be categorized according to two dimensions: 1) the cause of risk (known or unknown) and 2) the occurrence of risk (predictable or unpredictable). Based on our findings, we provide design implications for collaborative health technologies that support parents in better planning for contingencies and identifying unknown causes of risks together with their children. 

INTRODUCTION One of the central applications of the human reference genome has been to serve as a baseline for comparison in nearly all human genomic studies. Unfortunately, many difficult regions of the reference genome have remained unresolved for decades and are affected by collapsed duplications, missing sequences, and other issues. Relative to the current human reference genome, GRCh38, the Telomere-to-Telomere CHM13 (T2T-CHM13) genome closes all remaining gaps, adds nearly 200 million base pairs (Mbp) of sequence, corrects thousands of structural errors, and unlocks the most complex regions of the human genome for scientific inquiry. RATIONALE We demonstrate how the T2T-CHM13 reference genome universally improves read mapping and variant identification in a globally diverse cohort. This cohort includes all 3202 samples from the expanded 1000 Genomes Project (1KGP), sequenced with short reads, as well as 17 globally diverse samples sequenced with long reads. By applying state-of-the-art methods for calling single-nucleotide variants (SNVs) and structural variants (SVs), we document the strengths and limitations of T2T-CHM13 relative to its predecessors and highlight its promise for revealing new biological insights within technically challenging regions of the genome. RESULTS Across the 1KGP samples, we found more than 1 million additional high-quality variants genome-wide using T2T-CHM13 than with GRCh38. Within previously unresolved regions of the genome, we identified hundreds of thousands of variants per sample—a promising opportunity for evolutionary and biomedical discovery. T2T-CHM13 improves the Mendelian concordance rate among trios and eliminates tens of thousands of spurious SNVs per sample, including a reduction of false positives in 269 challenging, medically relevant genes by up to a factor of 12. These corrections are in large part due to improvements to 70 protein-coding genes in >9 Mbp of inaccurate sequence caused by falsely collapsed or duplicated regions in GRCh38. Using the T2T-CHM13 genome also yields a more comprehensive view of SVs genome-wide, with a greatly improved balance of insertions and deletions. Finally, by providing numerous resources for T2T-CHM13 (including 1KGP genotypes, accessibility masks, and prominent annotation databases), our work will facilitate the transition to T2T-CHM13 from the current reference genome. CONCLUSION The vast improvements in variant discovery across samples of diverse ancestries position T2T-CHM13 to succeed as the next prevailing reference for human genetics. T2T-CHM13 thus offers a model for the construction and study of high-quality reference genomes from globally diverse individuals, such as is now being pursued through collaboration with the Human Pangenome Reference Consortium. As a foundation, our work underscores the benefits of an accurate and complete reference genome for revealing diversity across human populations. Genomic features and resources available for T2T-CHM13. Comparisons to GRCh38 reveal broad improvements in SNVs, indels, and SVs discovered across diverse human populations by means of short-read (1KGP) and long-read sequencing (LRS). These improvements are due to resolution of complex genomic loci (nonsyntenic and previously unresolved), duplication errors, and discordant haplotypes, including those in medically relevant genes. 

Abstract The current human reference genome, GRCh38, represents over 20 years of effort to generate a high-quality assembly, which has benefitted society 1,2 . However, it still has many gaps and errors, and does not represent a biological genome as it is a blend of multiple individuals 3,4 . Recently, a high-quality telomere-to-telomere reference, CHM13, was generated with the latest long-read technologies, but it was derived from a hydatidiform mole cell line with a nearly homozygous genome 5 . To address these limitations, the Human Pangenome Reference Consortium formed with the goal of creating high-quality, cost-effective, diploid genome assemblies for a pangenome reference that represents human genetic diversity 6 . Here, in our first scientific report, we determined which combination of current genome sequencing and assembly approaches yield the most complete and accurate diploid genome assembly with minimal manual curation. Approaches that used highly accurate long reads and parent–child data with graph-based haplotype phasing during assembly outperformed those that did not. Developing a combination of the top-performing methods, we generated our first high-quality diploid reference assembly, containing only approximately four gaps per chromosome on average, with most chromosomes within ±1% of the length of CHM13. Nearly 48% of protein-coding genes have non-synonymous amino acid changes between haplotypes, and centromeric regions showed the highest diversity. Our findings serve as a foundation for assembling near-complete diploid human genomes at scale for a pangenome reference to capture global genetic variation from single nucleotides to structural rearrangements. 

Abstract High-quality and complete reference genome assemblies are fundamental for the application of genomics to biology, disease, and biodiversity conservation. However, such assemblies are available for only a few non-microbial species 1–4 . To address this issue, the international Genome 10K (G10K) consortium 5,6 has worked over a five-year period to evaluate and develop cost-effective methods for assembling highly accurate and nearly complete reference genomes. Here we present lessons learned from generating assemblies for 16 species that represent six major vertebrate lineages. We confirm that long-read sequencing technologies are essential for maximizing genome quality, and that unresolved complex repeats and haplotype heterozygosity are major sources of assembly error when not handled correctly. Our assemblies correct substantial errors, add missing sequence in some of the best historical reference genomes, and reveal biological discoveries. These include the identification of many false gene duplications, increases in gene sizes, chromosome rearrangements that are specific to lineages, a repeated independent chromosome breakpoint in bat genomes, and a canonical GC-rich pattern in protein-coding genes and their regulatory regions. Adopting these lessons, we have embarked on the Vertebrate Genomes Project (VGP), an international effort to generate high-quality, complete reference genomes for all of the roughly 70,000 extant vertebrate species and to help to enable a new era of discovery across the life sciences.