Biology subjects

Becker, W. R.

Publications and source records attributed to Becker, W. R..

8 recordsLinked to original sources

bioRxiv2025

Polyclonal origins of human premalignant colorectal lesions

Cancer is generally thought to be caused by expansion of a single mutant cell1. However, analyses of early colorectal cancer lesions suggest that tumors may instead originate from multiple, genetically distinct cell populations2,3. Detecting polyclonal tumor initiation is challenging in patients, as it requires profiling early-stage lesions before clonal sweeps obscure diversity. To investigate this, we analyzed normal colorectal mucosa, benign and dysplastic premalignant polyps, and malignant adenocarcinomas (123 samples) from six individuals with familial adenomatous polyposis (FAP). Individuals with FAP have a germline heterozygous APC mutation, predisposing them to colorectal cancer and numerous premalignant polyps by early adulthood4. Whole-genome and/or whole-exome sequencing revealed that many premalignant polyps--40% with benign histology and 28% with dysplasia--were composed of multiple genetic lineages that diverged early, consistent with polyclonal origins. This conclusion was reinforced by whole-genome sequencing of single crypts from multiple polyps in additional patients which showed limited sharing of mutations among crypts within the same lesion. In some cases, multiple distinct APC mutations co-existed in different lineages of a single polyp, consistent with polyclonality. These findings reshape our understanding of early neoplastic events, demonstrating that tumor initiation can arise from the convergence of diverse mutant clones. They also suggest that cell-intrinsic growth advantages alone may not fully explain tumor initiation, highlighting the importance of microenvironmental and tissue-level factors in early cancer evolution.

cancer biology↗

bioRxiv2024

Single-cell spatial mapping reveals alteration of cell type composition and tissue microenvironment during early colorectal cancer formation

Familial adenomatous polyposis (FAP) is a rare, hereditary syndrome that raises the risk of developing colorectal cancer (CRC). This disease model is well suited for studying the early stages of malignant transformation. Our spatial CODEX experiments reveal that, in contrast to normal mucosa, FAP mucosa, pre-cancer polyps and colorectal cancers exhibit substantial alterations in the cell type composition and tissue microenvironment. These early alterations include: an increase in the population of cancer-associated fibroblasts (CAFs), and the inhibition of tumor infiltrated lymphocytes and cell-adhesion protein by CAFs, the transformation of memory T cells into regulatory T cells, nuclear translocation of beta-catenin from the cell membrane, a decrease in the M1:M2 macrophage ratio, a notable increase in angiogenesis events. Our studies define the early stem cell, stromal, and immune steps of colorectal cancer and may benefit early detection, and therapeutic intervention.

cancer biology↗

bioRxiv2024

High-Throughput DNA melt measurements enable improved models of DNA folding thermodynamics

DNA folding thermodynamics are central to many biological processes and biotechnological applications involving base-pairing. Current methods for predicting stability from DNA sequence use nearest-neighbor models that struggle to accurately capture the diverse sequence-dependency of elements other than Watson-Crick base pairs, likely due to insufficient experimental data. We introduce a massively parallel method, Array Melt, that uses fluorescence-based quenching signals to measure equilibrium stability of millions of DNA hairpins simultaneously on a repurposed Illumina sequencing flow cell. By leveraging this dataset of 27,732 sequences with two-state melting behavior, we derived a refined NUPACK-compatible nearest-neighbor model, a richer parameterization nearest-neighbor model that exhibits higher accuracy, and a graph neural network (GNN) model that identifies relevant interactions within DNA beyond nearest neighbors. All models provide improved accuracy in predicting DNA folding thermodynamics, providing improvements relevant for in silico design of qPCR primers, oligo hybridization probes, and DNA origami.

biophysics↗

bioRxiv2021

High Resolution Single Cell Maps Reveals Distinct Cell Organization and Function Across Different Regions of the Human Intestine

The colon is a complex organ that promotes digestion, extracts nutrients, participates in immune surveillance, maintains critical symbiotic relationships with microbiota, and affects overall health. To better understand its organization, functions, and its regulation at a single cell level, we performed CODEX multiplexed imaging, as well as single nuclear RNA and open chromatin assays across eight different intestinal sites of four donors. Through systematic analyses we find cell compositions differ dramatically across regions of the intestine, demonstrate the complexity of epithelial subtypes, and find that the same cell types are organized into distinct neighborhoods and communities highlighting distinct immunological niches present in the intestine. We also map gene regulatory differences in these cells 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.

genomics↗

bioRxiv2021

Single-cell analyses reveal a continuum of cell state and composition changes in the malignant transformation of polyps to colorectal cancer

To chart cell composition and cell state changes that occur during the transformation of healthy colon to precancerous adenomas to colorectal cancer (CRC), we generated 451,886 single-cell chromatin accessibility profiles and 208,557 single-cell transcriptomes from 48 polyps, 27 normal tissues, and 6 CRCs collected from patients with and without germline APC mutations. A large fraction of polyp and CRC cells exhibit a stem-like phenotype, and we define a continuum of epigenetic and transcriptional changes occurring in these stem-like cells as they progress from normal to CRC. Advanced polyps contain increasing numbers of stem-like cells, regulatory T-cells, and a subtype of FOX-regulated pre-cancer associated fibroblasts. In the cancerous state, we observe T-cell exhaustion, RUNX1-regulated cancer associated fibroblasts, and increasing accessibility associated with HNF4A motifs in epithelia. Methylation changes in sporadic CRC are strongly anti-correlated with accessibility changes along this continuum, further identifying regulatory markers for molecular staging of polyps.

genomics↗

bioRxiv2020

Quantification of Cas9 binding and cleavage across diverse guide sequences maps landscapes of target engagement

The RNA-guided nuclease Cas9 has unlocked powerful methods for perturbing both the genome through targeted DNA cleavage and the regulome through targeted DNA binding, but limited biochemical data has hampered efforts to quantitatively model sequence perturbation of target binding and cleavage across diverse guide sequences. We present scalable, sequencing-based platforms for high-throughput filter binding and cleavage, then perform 62,444 quantitative binding and cleavage assays on 35,047 on- and off-target DNA sequences across 90 Cas9 ribonucleoproteins (RNPs) loaded with distinct guide RNAs. We observe that binding and cleavage efficacy, as well as specificity, vary substantially across RNPs; canonically studied guides often have atypically high specificity; sequence context surrounding the target significantly influences Cas9 on-rate; and Cas9 RNPs may sequester targets in nonproductive states that contribute to "proofreading" capability. Finally, we distill our findings into an interpretable biophysical model that predicts changes in binding and cleavage for diverse target sequence perturbations.

biochemistry↗

bioRxiv2019

Quantitative high-throughput tests of ubiquitous RNA secondary structure prediction algorithms via RNA/protein binding

Nearest-neighbor (NN) rules provide a simple and powerful quantitative framework for RNA structure prediction that is strongly supported for canonical Watson-Crick duplexes from a plethora of thermodynamic measurements. Predictions of RNA secondary structure based on nearest-neighbor (NN) rules are routinely used to understand biological function and to engineer and control new functions in biotechnology. However, NN applications to RNA structural features such as internal and terminal loops rely on approximations and assumptions, with sparse experimental coverage of the vast number of possible sequence and structural features. To test to what extent NN rules accurately predict thermodynamic stabilities across RNAs with non-WC features, we tested their predictions using a quantitative high-throughput assay platform, RNA-MaP. Using a thermodynamic assay with coupled protein binding, we carried out equilibrium measurements for over 1000 RNAs with a range of predicted secondary structure stabilities. Our results revealed substantial scatter and systematic deviations between NN predictions and observed stabilities. Solution salt effects and incorrect or omitted loop parameters contribute to these observed deviations. Our results demonstrate the need to independently and quantitatively test NN computational algorithms to identify their capabilities and limitations. RNA-MaP and related approaches can be used to test computational predictions and can be adapted to obtain experimental data to improve RNA secondary structure and other prediction algorithms.\n\nSignificance statementRNA secondary structure prediction algorithms are routinely used to understand, predict and design functional RNA structures in biology and biotechnology. Given the vast number of RNA sequence and structural features, these predictions rely on a series of approximations, and independent tests are needed to quantitatively evaluate the accuracy of predicted RNA structural stabilities. Here we measure the stabilities of over 1000 RNA constructs by using a coupled protein binding assay. Our results reveal substantial deviations from the RNA stabilities predicted by popular algorithms, and identify factors contributing to the observed deviations. We demonstrate the importance of quantitative, experimental tests of computational RNA structure predictions and present an approach that can be used to routinely test and improve the prediction accuracy.

biophysics↗

bioRxiv2018

A quantitative and predictive model for RNA binding by human Pumilio proteins

High-throughput methodologies have enabled routine generation of RNA target sets and sequence motifs for RNA-binding proteins (RBPs). Nevertheless, quantitative approaches are needed to capture the landscape of RNA/RBP interactions responsible for cellular regulation. We have used the RNA-MaP platform to directly measure equilibrium binding for thousands of designed RNAs and to construct a predictive model for RNA recognition by the human Pumilio proteins PUM1 and PUM2. Despite prior findings of linear sequence motifs, our measurements revealed widespread residue flipping and instances of positional coupling. Application of our thermodynamic model to published in vivo crosslinking data reveals quantitative agreement between predicted affinities and in vivo occupancies. Our analyses suggest a thermodynamically driven, continuous Pumilio binding landscape that is negligibly affected by RNA structure or kinetic factors, such as displacement by ribosomes. This work provides a quantitative foundation for dissecting the cellular behavior of RBPs and cellular features that impact their occupancies.

biochemistry↗