Daniel J Emerson, Peiyao A Zhao, Ashley L Cook, R Jordan Barnett, Kyle N Klein, Dalila Saulebekova, Chunmin Ge, Linda Zhou, Zoltan Simandi, Miriam K Minsk, Katelyn R Titus, Weitao Wang, Wanfeng Gong, Di Zhang, Liyan Yang, Sergey V Venev, Johan H Gibcus, Hongbo Yang, Takayo Sasaki, Masato T Kanemaki, Feng Yue, Job Dekker, Chun-Long Chen, David M Gilbert, Jennifer E Phillips-Cremins <<<

DNA replication occurs through an intricately regulated series of molecular events and is fundamental for genome stability. At present, it is unknown how the locations of replication origins are determined in the human genome. Here we dissect the role of topologically associating domains (TADs), subTADs and loops in the positioning of replication initiation zones (IZs). We stratify TADs and subTADs by the presence of corner-dots indicative of loops and the orientation of CTCF motifs. We find that high-efficiency, early replicating IZs localize to boundaries between adjacent corner-dot TADs anchored by high-density arrays of divergently and convergently oriented CTCF motifs. By contrast, low-efficiency IZs localize to weaker dotless boundaries. Following ablation of cohesin-mediated loop extrusion during G1, high-efficiency IZs become diffuse and delocalized at boundaries with complex CTCF motif orientations. Moreover, G1 knockdown of the cohesin unloading factor WAPL results in gained long-range loops and narrowed localization of IZs at the same boundaries. Finally, targeted deletion or insertion of specific boundaries causes local replication timing shifts consistent with IZ loss or gain, respectively. Our data support a model in which cohesin-mediated loop extrusion and stalling at a subset of genetically encoded TAD and subTAD boundaries is an essential determinant of the locations of replication origins in human S phase. <<<

Jacqueline Rehner, Georges Pierre Schmartz, Laura Groeger, Jan Dastbaz, Nicole Ludwig, Matthias Hannig, Stefan Rupf, Berthold Seitz, Elias Flockerzi, Tim Berger, Matthias Christian Reichert, Marcin Krawczyk, Eckart Meese, Christian Herr, Robert Bals, Sören L Becker, Andreas Keller, Rolf Müller, IMAGINE Consortium <<<

High-quality DNA extraction is a crucial step in metagenomic studies. Bias by different isolation kits impairs the comparison across datasets. A trending topic is, however, the analysis of multiple metagenomes from the same patients to draw a holistic picture of microbiota associated with diseases. We thus collected bile, stool, saliva, plaque, sputum, and conjunctival swab samples and performed DNA extraction with three commercial kits. For each combination of the specimen type and DNA extraction kit, 20-gigabase (Gb) metagenomic data were generated using short-read sequencing. While profiles of the specimen types showed close proximity to each other, we observed notable differences in the alpha diversity and composition of the microbiota depending on the DNA extraction kits. No kit outperformed all selected kits on every specimen. We reached consistently good results using the Qiagen QiAamp DNA Microbiome Kit. Depending on the specimen, our data indicate that over 10 Gb of sequencing data are required to achieve sufficient resolution, but DNA-based identification is superior to identification by mass spectrometry. Finally, long-read nanopore sequencing confirmed the results (correlation coefficient > 0.98). Our results thus suggest using a strategy with only one kit for studies aiming for a direct comparison of multiple microbiotas from the same patients. <<<

Conventional environmental health studies have primarily focused on limited environmental stressors at the population level, which lacks the power to dissect the complexity and heterogeneity of individualized environmental exposures. Here, as a pilot case study, we integrated deep-profiled longitudinal personal exposome and internal multi-omics to systematically investigate how the exposome shapes a single individual's phenome. We annotated thousands of chemical and biological components in the personal exposome cloud and found they were significantly correlated with thousands of internal biomolecules, which was further cross-validated using corresponding clinical data. Our results showed that agrochemicals and fungi predominated in the highly diverse and dynamic personal exposome, and the biomolecules and pathways related to the individual's immune system, kidney, and liver were highly associated with the personal external exposome. Overall, this data-driven longitudinal monitoring study shows the potential dynamic interactions between the personal exposome and internal multi-omics, as well as the impact of the exposome on precision health by producing abundant testable hypotheses. <<<

The synthetic yeast, Sc2.0, is nearing completion as consolidation of all 17 synthetic chromosomes into a single cell advances. This organism will be the first synthetic eukaryote and provides a highly plastic biological chassis built from the bottom-up using principles of biological design. This synthetic approach to genome construction has allowed the genetic code to be re-wired in this background to liberate the amber stop codon as a dedicated triplet for encoding non-canonical amino acids. The availability of an expanded set of amino acid building blocks allows precise control of protein structure and function, providing new opportunities to develop protein-based therapeutics, materials and catalysts. In this article, we review the challenges facing genetic code expansion research in yeast and highlight how the development of Sc2.0 provides new and exciting opportunities to address existing limitations. <<<

Frameshift mutations have been considered of significant importance for the molecular evolution of proteins and their coding genes, while frameshift protein sequences encoded in the alternative reading frames of coding genes have been considered to be meaningless. However, functional frameshifts have been found widely existing. It was puzzling how a frameshift protein kept its structure and functionality while substantial changes occurred in its primary amino-acid sequence. This study shows that the similarities among frameshifts and wild types are higher than random similarities and are determined at different levels. Frameshift substitutions are more conservative than random substitutions in the standard genetic code (SGC). The frameshift substitutions score of SGC ranks in the top 2.0-3.5% of alternative genetic codes, showing that SGC is nearly optimal for frameshift tolerance. In many genes and certain genomes, frameshift-resistant codons and codon pairs appear more frequently than expected, suggesting that frameshift tolerance is achieved through not only the optimality of the genetic code but, more importantly, the further optimization of a specific gene or genome through the usages of codons/codon pairs, which sheds light on the role of frameshift mutations in molecular and genomic evolution. <<<

Bonnie E Gould Rothberg, Tammie E Quest, Sai-Ching J Yeung, Lorraine C Pelosof, David E Gerber, Justin A Seltzer, Jason J Bischof, Charles R Thomas, Nausheen Akhter, Mira Mamtani, Robin E Stutman, Christopher W Baugh, Venkataraman Anantharaman, Nicholas R Pettit, Adam D Klotz, Michael A Gibbs, Demetrios N Kyriacou <<<

Patients with advanced cancer generate 4 million visits annually to emergency departments (EDs) and other dedicated, high-acuity oncology urgent care centers. Because of both the increasing complexity of systemic treatments overall and the higher rates of active therapy in the geriatric population, many patients experiencing acute decompensations are frail and acutely ill. This article comprehensively reviews the spectrum of oncologic emergencies and urgencies typically encountered in acute care settings. Presentation, underlying etiology, and up-to-date clinical pathways are discussed. Criteria for either a safe discharge to home or a transition of care to the inpatient oncology hospitalist team are emphasized. This review extends beyond familiar conditions such as febrile neutropenia, hypercalcemia, tumor lysis syndrome, malignant spinal cord compression, mechanical bowel obstruction, and breakthrough pain crises to include a broader spectrum of topics encompassing the syndrome of inappropriate antidiuretic hormone secretion, venous thromboembolism and malignant effusions, as well as chemotherapy-induced mucositis, cardiomyopathy, nausea, vomiting, and diarrhea. Emergent and urgent complications associated with targeted therapeutics, including small molecules, naked and drug-conjugated monoclonal antibodies, as well as immune checkpoint inhibitors and chimeric antigen receptor T-cells, are summarized. Finally, strategies for facilitating same-day direct admission to hospice from the ED are discussed. This article not only can serve as a point-of-care reference for the ED physician but also can assist outpatient oncologists as well as inpatient hospitalists in coordinating care around the ED visit. <<<

Chromosome replication is performed by a complex and intricate ensemble of proteins termed the replisome, where the DNA polymerases Polδ and Polε, DNA polymerase α-primase (Polα) and accessory proteins including AND-1, CLASPIN and TIMELESS-TIPIN (respectively known as Ctf4, Mrc1 and Tof1-Csm3 in Saccharomyces cerevisiae) are organized around the CDC45-MCM-GINS (CMG) replicative helicase. Because a functional human replisome has not been reconstituted from purified proteins, how these factors contribute to human DNA replication and whether additional proteins are required for optimal DNA synthesis are poorly understood. Here we report the biochemical reconstitution of human replisomes that perform fast and efficient DNA replication using 11 purified human replication factors made from 43 polypeptides. Polε, but not Polδ, is crucial for optimal leading-strand synthesis. Unexpectedly, Polε-mediated leading-strand replication is highly dependent on the sliding-clamp processivity factor PCNA and the alternative clamp loader complex CTF18-RFC. We show how CLASPIN and TIMELESS-TIPIN contribute to replisome progression and demonstrate that, in contrast to the budding yeast replisome, AND-1 directly augments leading-strand replication. Moreover, although AND-1 binds to Polα, the interaction is dispensable for lagging-strand replication, indicating that Polα is functionally recruited via an AND-1-independent mechanism for priming in the human replisome. Collectively, our work reveals how the human replisome achieves fast and efficient leading-strand and lagging-strand DNA replication, and provides a powerful system for future studies of the human replisome and its interactions with other DNA metabolic processes. <<<

Allele-specific expression (ASE) is a phenomenon in which one allele is preferentially expressed over the other. Genetic and epigenetic factors cause ASE by altering the final composition of a gene's product, leading to expression imbalances that can have functional consequences on phenotypes. Environmental signals also impact allele-specific expression, but how they contribute to this cross talk remains understudied. Here, we explored how genotype, parent-of-origin, tissue, sex, and dietary fat simultaneously influence ASE biases. Male and female mice from a F reciprocal cross of the LG/J and SM/J strains were fed a high or low fat diet. We harnessed strain-specific variants to distinguish between two ASE classes: parent-of-origin-dependent (unequal expression based on parental origin) and sequence-dependent (unequal expression based on nucleotide identity). We present a comprehensive map of ASE patterns in 2853 genes across three tissues and nine environmental contexts. We found that both ASE classes are highly dependent on tissue and environmental context. They vary across metabolically relevant tissues, between males and females, and in response to dietary fat. We also found 45 genes with inconsistent ASE biases that switched direction across tissues and/or environments. Finally, we integrated ASE and QTL data from published intercrosses of the LG/J and SM/J strains. Our ASE genes are often enriched in QTLs for metabolic and musculoskeletal traits, highlighting how this orthogonal approach can prioritize candidate genes. Together, our results provide novel insights into how genetic, epigenetic, and environmental mechanisms govern allele-specific expression, which is an essential step toward deciphering the genotype-to-phenotype map. <<<

We introduce a massively parallel novel sequencing platform that combines an open flow cell design on a circular wafer with a large surface area and mostly natural nucleotides that allow optical end-point detection without reversible terminators. This platform enables sequencing billions of reads with longer read length (~300bp) and fast runs times (<20hrs) with high base accuracy (Q30 > 85%), at a low cost of $1/Gb. We establish system performance by whole-genome sequencing of the Genome-In-A-Bottle reference samples HG001-7, demonstrating high accuracy for SNPs (99.6%) and Indels in homopolymers up to length 10 (96.4%) across the vast majority (>98%) of the defined high-confidence regions of these samples. We demonstrate scalability of the whole-genome sequencing workflow by sequencing an additional 224 selected samples from the 1000 Genomes project achieving high concordance with reference data. <<<

Stefanie Warnat-Herresthal, Hartmut Schultze, Krishnaprasad Lingadahalli Shastry, Sathyanarayanan Manamohan, Saikat Mukherjee, Vishesh Garg, Ravi Sarveswara, Kristian Händler, Peter Pickkers, N Ahmad Aziz, Sofia Ktena, Florian Tran, Michael Bitzer, Stephan Ossowski, Nicolas Casadei, Christian Herr, Daniel Petersheim, Uta Behrends, Fabian Kern, Tobias Fehlmann, Philipp Schommers, Clara Lehmann, Max Augustin, Jan Rybniker, Janine Altmüller, Neha Mishra, Joana P Bernardes, Benjamin Krämer, Lorenzo Bonaguro, Jonas Schulte-Schrepping, Elena De Domenico, Christian Siever, Michael Kraut, Milind Desai, Bruno Monnet, Maria Saridaki, Charles Martin Siegel, Anna Drews, Melanie Nuesch-Germano, Heidi Theis, Jan Heyckendorf, Stefan Schreiber, Sarah Kim-Hellmuth, COVID-19 Aachen Study (COVAS), Jacob Nattermann, Dirk Skowasch, Ingo Kurth, Andreas Keller, Robert Bals, Peter Nürnberg, Olaf Rieß, Philip Rosenstiel, Mihai G Netea, Fabian Theis, Sach Mukherjee, Michael Backes, Anna C Aschenbrenner, Thomas Ulas, Deutsche COVID-19 Omics Initiative (DeCOI), Monique M B Breteler, Evangelos J Giamarellos-Bourboulis, Matthijs Kox, Matthias Becker, Sorin Cheran, Michael S Woodacre, Eng Lim Goh, Joachim L Schultze <<<

Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine. Patients with leukaemia can be identified using machine learning on the basis of their blood transcriptomes. However, there is an increasing divide between what is technically possible and what is allowed, because of privacy legislation. Here, to facilitate the integration of any medical data from any data owner worldwide without violating privacy laws, we introduce Swarm Learning-a decentralized machine-learning approach that unites edge computing, blockchain-based peer-to-peer networking and coordination while maintaining confidentiality without the need for a central coordinator, thereby going beyond federated learning. To illustrate the feasibility of using Swarm Learning to develop disease classifiers using distributed data, we chose four use cases of heterogeneous diseases (COVID-19, tuberculosis, leukaemia and lung pathologies). With more than 16,400 blood transcriptomes derived from 127 clinical studies with non-uniform distributions of cases and controls and substantial study biases, as well as more than 95,000 chest X-ray images, we show that Swarm Learning classifiers outperform those developed at individual sites. In addition, Swarm Learning completely fulfils local confidentiality regulations by design. We believe that this approach will notably accelerate the introduction of precision medicine. <<<

Denise M Wolf, Christina Yau, Julia Wulfkuhle, Lamorna Brown-Swigart, Rosa I Gallagher, Pei Rong Evelyn Lee, Zelos Zhu, Mark J Magbanua, Rosalyn Sayaman, Nicholas O'Grady, Amrita Basu, Amy Delson, Jean Philippe Coppé, Ruixiao Lu, Jerome Braun, I-SPY2 Investigators, Smita M Asare, Laura Sit, Jeffrey B Matthews, Jane Perlmutter, Nola Hylton, Minetta C Liu, Paula Pohlmann, W Fraser Symmans, Hope S Rugo, Claudine Isaacs, Angela M DeMichele, Douglas Yee, Donald A Berry, Lajos Pusztai, Emanuel F Petricoin, Gillian L Hirst, Laura J Esserman, Laura J van 't Veer <<<

Using pre-treatment gene expression, protein/phosphoprotein, and clinical data from the I-SPY2 neoadjuvant platform trial (NCT01042379), we create alternative breast cancer subtypes incorporating tumor biology beyond clinical hormone receptor (HR) and human epidermal growth factor receptor-2 (HER2) status to better predict drug responses. We assess the predictive performance of mechanism-of-action biomarkers from ∼990 patients treated with 10 regimens targeting diverse biology. We explore >11 subtyping schemas and identify treatment-subtype pairs maximizing the pathologic complete response (pCR) rate over the population. The best performing schemas incorporate Immune, DNA repair, and HER2/Luminal phenotypes. Subsequent treatment allocation increases the overall pCR rate to 63% from 51% using HR/HER2-based treatment selection. pCR gains from reclassification and improved patient selection are highest in HR subsets (>15%). As new treatments are introduced, the subtyping schema determines the minimum response needed to show efficacy. This data platform provides an unprecedented resource and supports the usage of response-based subtypes to guide future treatment prioritization. <<<

The translational challenges in the field of precision oncology are in part related to the biological complexity and diversity of this disease. Technological advances in genomics have facilitated large sequencing efforts and discoveries that have further supported this notion. In this review, we reflect on the impact of these discoveries on our understanding of several concepts: cancer initiation, cancer prevention, early detection, adjuvant therapy and minimal residual disease monitoring, cancer drug resistance, and cancer evolution in metastasis. We discuss key areas of focus for improving cancer outcomes, from biological insights to clinical application, and suggest where the development of these technologies will lead us. Finally, we discuss practical challenges to the wider adoption of molecular profiling in the clinic and the need for robust translational infrastructure. <<<

In the past 5 years transcriptome or RNA-sequencing (RNA-seq) has steadily emerged as a complementary assay for rare disease diagnosis and discovery. In this perspective, we summarize several recent developments and challenges in the use of RNA-seq for rare disease investigation. Using an accessible patient sample, such as blood, skin, or muscle, RNA-seq enables the assay of expressed RNA transcripts. Analysis of RNA-seq allows the identification of aberrant or outlier gene expression and alternative splicing as functional evidence to support rare disease study and diagnosis. Further, many types of variant effects can be profiled beyond coding variants, as the consequences of noncoding variants that impact gene expression and splicing can be directly observed. This is particularly apparent for structural variants that disproportionately underlie outlier gene expression and for splicing variants in which RNA-seq can both measure aberrant canonical splicing and detect deep intronic effects. However, a major potential limitation of RNA-seq in rare disease investigation is the developmental and cell type specificity of gene expression as a pathogenic variant's effect may be limited to a specific spatiotemporal context and access to a patient's tissue sample from the relevant tissue and timing of disease expression may not be possible. We speculate that as advances in computational methods and emerging experimental techniques overcome both developmental and cell type specificity, there will be broadening use of RNA sequencing and multiomics in rare disease diagnosis and delivery of precision health. <<<

Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths in the United States and compiles the most recent data on population-based cancer occurrence and outcomes. Incidence data (through 2018) were collected by the Surveillance, Epidemiology, and End Results program; the National Program of Cancer Registries; and the North American Association of Central Cancer Registries. Mortality data (through 2019) were collected by the National Center for Health Statistics. In 2022, 1,918,030 new cancer cases and 609,360 cancer deaths are projected to occur in the United States, including approximately 350 deaths per day from lung cancer, the leading cause of cancer death. Incidence during 2014 through 2018 continued a slow increase for female breast cancer (by 0.5% annually) and remained stable for prostate cancer, despite a 4% to 6% annual increase for advanced disease since 2011. Consequently, the proportion of prostate cancer diagnosed at a distant stage increased from 3.9% to 8.2% over the past decade. In contrast, lung cancer incidence continued to decline steeply for advanced disease while rates for localized-stage increased suddenly by 4.5% annually, contributing to gains both in the proportion of localized-stage diagnoses (from 17% in 2004 to 28% in 2018) and 3-year relative survival (from 21% to 31%). Mortality patterns reflect incidence trends, with declines accelerating for lung cancer, slowing for breast cancer, and stabilizing for prostate cancer. In summary, progress has stagnated for breast and prostate cancers but strengthened for lung cancer, coinciding with changes in medical practice related to cancer screening and/or treatment. More targeted cancer control interventions and investment in improved early detection and treatment would facilitate reductions in cancer mortality. <<<