Segmentation of human functional tissue units in support of a Human Reference Atlas

The Human BioMolecular Atlas Program (HuBMAP) aims to compile a Human Reference Atlas (HRA) for the healthy adult body at the cellular level. Functional tissue units (FTUs), relevant for HRA construction, are of pathobiological significance. Manual segmentation of FTUs does not scale; highly accurate and performant, open-source machine-learning algorithms are needed. We designed and hosted a Kaggle competition that focused on development of such algorithms and 1200 teams from 60 countries participated. We present the competition outcomes and an expanded analysis of the winning algorithms on additional kidney and colon tissue data, and conduct a pilot study to understand spatial location and density of FTUs across the kidney. The top algorithm from the competition, Tom, outperforms other algorithms in the expanded study, while using fewer computational resources. Tom was added to the HuBMAP infrastructure to run kidney FTU segmentation at scale-showcasing the value of Kaggle competitions for advancing research.

Organization of the human intestine at single-cell resolution

The intestine is a complex organ that promotes digestion, extracts nutrients, participates in immune surveillance, maintains critical symbiotic relationships with microbiota and affects overall health1. The intesting has a length of over nine metres, along which there are differences in structure and function2. The localization of individual cell types, cell type development trajectories and detailed cell transcriptional programs probably drive these differences in function. Here, to better understand these differences, we evaluated the organization of single cells using multiplexed imaging and single-nucleus RNA and open chromatin assays across eight different intestinal sites from nine donors. Through systematic analyses, we find cell compositions that differ substantially across regions of the intestine and demonstrate the complexity of epithelial subtypes, and find that the same cell types are organized into distinct neighbourhoods and communities, highlighting distinct immunological niches that are present in the intestine. We also map gene regulatory differences in these cells that are suggestive of a regulatory differentiation cascade, and associate intestinal disease heritability with specific cell types. These results describe the complexity of the cell composition, regulation and organization for this organ, and serve as an important reference map for understanding human biology and disease.

Abstract 2706: Ultra-Low Input High-Fidelity (ULI-HiFi) long-reads uncover variants in genomic dark matter from pre-cancer polyp and tumor samples

Long-read sequencing technologies have been constrained by high error rates and large sample input requirements. The recent introduction of HiFi sequencing has enabled highly accurate detection of single-nucleotide variants (SNVs) from long reads (10-15 kb). However, a major limiting factor is the amount of sample input required, where current protocols require ≥15 micrograms of DNA. Here we report Ultra-Low Input High Fidelity Sequencing (ULI-HiFi), an amplification-based library preparation that reduces this input to 10 nanograms of DNA, a more than 10,000-fold reduction in sample input. When the ultra-low input method was tested using a benchmark genome, HG002, we observed high precision and improved recall of structural variants compared to a ground truth dataset from the Genome in a Bottle Consortium. We also benchmarked small variants and reported the accurate analysis of many variants in clinically important genes that are unmappable with short reads. We used this strategy to sequence tumor and polyp samples from a patient with familial adenomatous polyposis, a hereditary form of colon cancer, which revealed SNVs and structural variants not detected by short-read techniques. This strategy will enable the improved characterization of genetic variants from limited clinical samples.

Citation Format: Hayan Lee, Graham Erwin, Aaron Horning, Raushun Kirtikar, Emmett Griffin-Baldwin, William Rowell, Philip Li, Sarah Kingan, Michael P. Snyder. Ultra-Low Input High-Fidelity (ULI-HiFi) long-reads uncover variants in genomic dark matter from pre-cancer polyp and tumor samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2706.

Global, distinctive, and personal changes in molecular and microbial profiles by specific fibers in humans

Dietary fibers act through the microbiome to improve cardiovascular health and prevent metabolic disorders and cancer. To understand the health benefits of dietary fiber supplementation, we investigated two popular purified fibers, arabinoxylan (AX) and long-chain inulin (LCI), and a mixture of five fibers. We present multiomic signatures of metabolomics, lipidomics, proteomics, metagenomics, a cytokine panel, and clinical measurements on healthy and insulin-resistant participants. Each fiber is associated with fiber-dependent biochemical and microbial responses. AX consumption associates with a significant reduction in LDL and an increase in bile acids, contributing to its observed cholesterol reduction. LCI is associated with an increase in Bifidobacterium. However, at the highest LCI dose, there is increased inflammation and elevation in the liver enzyme alanine aminotransferase. This study yields insights into the effects of fiber supplementation and the mechanisms behind fiber-induced cholesterol reduction, and it shows effects of individual, purified fibers on the microbiome.

The human body at cellular resolution: the NIH Human Biomolecular Atlas Program

Transformative technologies are enabling the construction of three-dimensional maps of tissues with unprecedented spatial and molecular resolution. Over the next seven years, the NIH Common Fund Human Biomolecular Atlas Program (HuBMAP) intends to develop a widely accessible framework for comprehensively mapping the human body at single-cell resolution by supporting technology development, data acquisition, and detailed spatial mapping. HuBMAP will integrate its efforts with other funding agencies, programs, consortia, and the biomedical research community at large towards the shared vision of a comprehensive, accessible three-dimensional molecular and cellular atlas of the human body, in health and under various disease conditions.