scholarly journals Single-Cell Technologies to Study Phenotypic Heterogeneity and Bacterial Persisters

2021 ◽  
Vol 9 (11) ◽  
pp. 2277
Author(s):  
Patricia J. Hare ◽  
Travis J. LaGree ◽  
Brandon A. Byrd ◽  
Angela M. DeMarco ◽  
Wendy W. K. Mok
Keyword(s):  
Single Cell ◽  
Bacterial Population ◽  
Molecular Mechanisms ◽  
Phenotypic Heterogeneity ◽  
Disease Treatment ◽  
Cellular Processes ◽  
Fluorescent Tags ◽  
Rare Cells ◽  
Content Information ◽  
Generation Sequencing

Antibiotic persistence is a phenomenon in which rare cells of a clonal bacterial population can survive antibiotic doses that kill their kin, even though the entire population is genetically susceptible. With antibiotic treatment failure on the rise, there is growing interest in understanding the molecular mechanisms underlying bacterial phenotypic heterogeneity and antibiotic persistence. However, elucidating these rare cell states can be technically challenging. The advent of single-cell techniques has enabled us to observe and quantitatively investigate individual cells in complex, phenotypically heterogeneous populations. In this review, we will discuss current technologies for studying persister phenotypes, including fluorescent tags and biosensors used to elucidate cellular processes; advances in flow cytometry, mass spectrometry, Raman spectroscopy, and microfluidics that contribute high-throughput and high-content information; and next-generation sequencing for powerful insights into genetic and transcriptomic programs. We will further discuss existing knowledge gaps, cutting-edge technologies that can address them, and how advances in single-cell microbiology can potentially improve infectious disease treatment outcomes.

scholarly journals Heteroresistance at the Single-Cell Level: Adapting to Antibiotic Stress through a Population-Based Strategy and Growth-Controlled Interphenotypic Coordination

mBio ◽  
2014 ◽  
Vol 5 (1) ◽  
Author(s):  
Xiaorong Wang ◽  
Yu Kang ◽  
Chunxiong Luo ◽  
Tong Zhao ◽  
Lin Liu ◽  
...  
Keyword(s):  
Growth Rate ◽  
Single Cell ◽  
Task Allocation ◽  
Bacterial Population ◽  
Population Based ◽  
Phenotypic Heterogeneity ◽  
Single Cell Level ◽  
Bacterial Survival ◽  
Cell Level ◽  
Resistant Cells

ABSTRACT Heteroresistance refers to phenotypic heterogeneity of microbial clonal populations under antibiotic stress, and it has been thought to be an allocation of a subset of “resistant” cells for surviving in higher concentrations of antibiotic. The assumption fits the so-called bet-hedging strategy, where a bacterial population “hedges” its “bet” on different phenotypes to be selected by unpredicted environment stresses. To test this hypothesis, we constructed a heteroresistance model by introducing a bla CTX-M-14 gene (coding for a cephalosporin hydrolase) into a sensitive Escherichia coli strain. We confirmed heteroresistance in this clone and that a subset of the cells expressed more hydrolase and formed more colonies in the presence of ceftriaxone (exhibited stronger “resistance”). However, subsequent single-cell-level investigation by using a microfluidic device showed that a subset of cells with a distinguishable phenotype of slowed growth and intensified hydrolase expression emerged, and they were not positively selected but increased their proportion in the population with ascending antibiotic concentrations. Therefore, heteroresistance—the gradually decreased colony-forming capability in the presence of antibiotic—was a result of a decreased growth rate rather than of selection for resistant cells. Using a mock strain without the resistance gene, we further demonstrated the existence of two nested growth-centric feedback loops that control the expression of the hydrolase and maximize population growth in various antibiotic concentrations. In conclusion, phenotypic heterogeneity is a population-based strategy beneficial for bacterial survival and propagation through task allocation and interphenotypic collaboration, and the growth rate provides a critical control for the expression of stress-related genes and an essential mechanism in responding to environmental stresses. IMPORTANCE Heteroresistance is essentially phenotypic heterogeneity, where a population-based strategy is thought to be at work, being assumed to be variable cell-to-cell resistance to be selected under antibiotic stress. Exact mechanisms of heteroresistance and its roles in adaptation to antibiotic stress have yet to be fully understood at the molecular and single-cell levels. In our study, we have not been able to detect any apparent subset of “resistant” cells selected by antibiotics; on the contrary, cell populations differentiate into phenotypic subsets with variable growth statuses and hydrolase expression. The growth rate appears to be sensitive to stress intensity and plays a key role in controlling hydrolase expression at both the bulk population and single-cell levels. We have shown here, for the first time, that phenotypic heterogeneity can be beneficial to a growing bacterial population through task allocation and interphenotypic collaboration other than partitioning cells into different categories of selective advantage.

scholarly journals Single-Cell RNA Sequencing Defines the Regulation of Spermatogenesis by Sertoli-Cell Androgen Signaling

2021 ◽  
Vol 9 ◽  
Author(s):  
Congcong Cao ◽  
Qian Ma ◽  
Shaomei Mo ◽  
Ge Shu ◽  
Qunlong Liu ◽  
...  
Keyword(s):  
Single Cell ◽  
Sertoli Cells ◽  
Molecular Mechanisms ◽  
Cell Types ◽  
Cellular Heterogeneity ◽  
Cell Populations ◽  
Wild Type ◽  
Cellular Processes ◽  
Transcriptomic Sequencing ◽  
Transcriptional Changes

Androgen receptor (AR) signaling is essential for maintaining spermatogenesis and male fertility. However, the molecular mechanisms by which AR acts between male germ cells and somatic cells during spermatogenesis have not begun to be revealed until recently. With the advances obtained from the use of transgenic mice lacking AR in Sertoli cells (SCARKO) and single-cell transcriptomic sequencing (scRNA-seq), the cell specific targets of AR action as well as the genes and signaling pathways that are regulated by AR are being identified. In this study, we collected scRNA-seq data from wild-type (WT) and SCARKO mice testes at p20 and identified four somatic cell populations and two male germ cell populations. Further analysis identified that the distribution of Sertoli cells was completely different and uncovered the cellular heterogeneity and transcriptional changes between WT and SCARKO Sertoli cells. In addition, several differentially expressed genes (DEGs) in SCARKO Sertoli cells, many of which have been previously implicated in cell cycle, apoptosis and male infertility, have also been identified. Together, our research explores a novel perspective on the changes in the transcription level of various cell types between WT and SCARKO mice testes, providing new insights for the investigations of the molecular and cellular processes regulated by AR signaling in Sertoli cells.

ON SIMULATING THE GENERATION OF MOSAICISM DURING MAMMALIAN CEREBRAL CORTICAL DEVELOPMENT

2009 ◽  
Vol 17 (01) ◽  
pp. 27-62 ◽  
Author(s):  
MICHAEL A. CASE ◽  
HUGH R. MACMILLAN
Keyword(s):  
Decision Making ◽  
Single Cell ◽  
Cell Fate ◽  
Cell Population ◽  
Cellular Response ◽  
Molecular Mechanisms ◽  
Cortical Development ◽  
Coarse Grained ◽  
Biological Organization ◽  
Cellular Processes

Renewed calls for a systems biology reflect the hope hat enduring biological questions at single-cell and cell-population scales will be resolved as modern molecular biology, with its reductionist program, approaches a nearly-complete characterization of the molecular mechanisms of specific cellular processes. Due to the confounding complexity of biological organization across these scales, computational science is sought to complement the intuition of experimentalists. However, with respect to the molecular basis of cellular processes during development and disease, a gulf between feasible simulations and realistic biology persists. Formidable are the mathematical and computational challenges to conducting and validating cell population-scale simulations, drawn from single-cell level and molecular level details. Nonetheless, in some biological contexts, a focus on core processes crafted by evolution can yield coarse-grained mathematical models that retain explanatory potential despite drastic simplification of known biochemical kinetics. In this article, we bring this modeling philosophy to bear on the nature of neural progenitor cell decision making during mammalian cerebral cortical development. Specifically, we present the computational component to a research program addressing developmental links between (i) the cellular response to endogenous DNA damage, (ii) primary mechanisms of neuronal genetic heterogeneity, or mosaicism, and (iii) the cell fate decision making that defines the population kinetics of neurogenesis.

scholarly journals GeneTrail: A Framework for the Analysis of High-Throughput Profiles

2021 ◽  
Vol 8 ◽  
Author(s):  
Nico Gerstner ◽  
Tim Kehl ◽  
Kerstin Lenhof ◽  
Lea Eckhart ◽  
Lara Schneider ◽  
...  
Keyword(s):  
Single Cell ◽  
High Throughput ◽  
Molecular Mechanisms ◽  
State Of The Art ◽  
High Dimensional ◽  
Data Sets ◽  
Biological Processes ◽  
Data Set ◽  
Rich Functionality ◽  
Generation Sequencing

Experimental high-throughput techniques, like next-generation sequencing or microarrays, are nowadays routinely applied to create detailed molecular profiles of cells. In general, these platforms generate high-dimensional and noisy data sets. For their analysis, powerful bioinformatics tools are required to gain novel insights into the biological processes under investigation. Here, we present an overview of the GeneTrail tool suite that offers rich functionality for the analysis and visualization of (epi-)genomic, transcriptomic, miRNomic, and proteomic profiles. Our framework enables the analysis of standard bulk, time-series, and single-cell measurements and includes various state-of-the-art methods to identify potentially deregulated biological processes and to detect driving factors within those deregulated processes. We highlight the capabilities of our web service with an analysis of a single-cell COVID-19 data set that demonstrates its potential for uncovering complex molecular mechanisms.GeneTrail can be accessed freely and without login requirements at http://genetrail.bioinf.uni-sb.de.

scholarly journals Understanding the pathogenesis of infectious diseases by single-cell RNA sequencing

2021 ◽  
Vol 8 (9) ◽  
pp. 208-222
Author(s):  
Wanqiu Huang ◽  
Danni Wang ◽  
Yu-Feng Yao
Keyword(s):  
Infectious Diseases ◽  
Single Cell ◽  
Rna Sequencing ◽  
Molecular Mechanisms ◽  
Transcriptional Profiling ◽  
Single Cell Level ◽  
Cell Level ◽  
Disease Treatment ◽  
Single Cell Rna Sequencing ◽  
Cell Diversity

Infections are highly orchestrated and dynamic processes, which involve both pathogen and host. Transcriptional profiling at the single-cell level enables the analysis of cell diversity, heterogeneity of the immune response, and detailed molecular mechanisms underlying infectious diseases caused by bacteria, viruses, fungi, and parasites. Herein, we highlight recent remarkable advances in single-cell RNA sequencing (scRNA-seq) technologies and their applications in the investigation of host-pathogen interactions, current challenges and potential prospects for disease treatment are discussed as well. We propose that with the aid of scRNA-seq, the mechanism of infectious diseases will be further revealed thus inspiring the development of novel interventions and therapies.

scholarly journals Functional single cell selection and annotated profiling of dynamically changing cancer cells

2021 ◽  
Author(s):  
Li You ◽  
Pin-Rui Su ◽  
Max Betjes ◽  
Reza Ghadiri Rad ◽  
Ting-Chun Chou ◽  
...  
Keyword(s):  
Single Cell ◽  
Cancer Biology ◽  
Molecular Mechanisms ◽  
State Of The Art ◽  
Automated Image Analysis ◽  
Cell Selection ◽  
Single Cell Sequencing ◽  
Functional Dynamics ◽  
Rare Cells ◽  
Mcf10a Cells

A method connecting single cell genomic or transcriptomic profiles to functional cellular characteristics, in particular time-varying phenotypic changes, would be transformative for single cell and cancer biology. Here, we present fSCS: functional single cell selection. This technology combines a custom-built ultrawide field-of-view optical screening microscope, fast automated image analysis and a new photolabeling method, phototagging, using a newly synthesized visible-light-photoactivatable dye. Using fSCS, we screen, selectively photolabel and isolate cells of interest from large heterogeneous populations based on functional dynamics like fast migration, morphological variation, small molecule uptake or cell division. We combined fSCS with single cell RNA sequencing for functionally annotated transcriptomic profiling of fast migrating and spindle-shaped MCF10A cells with or without TGFβ induction. We identified critical genes and pathways driving aggressive migration as well as mesenchymal-like morphology that could not be detected with state-of-the-art single cell transcriptomic analysis. fSCS provides a crucial upstream selection paradigm for single cell sequencing independent of biomarkers, allows enrichment of rare cells and can facilitate the identification and understanding of molecular mechanisms underlying functional phenotypes.

scholarly journals Role of Long Non-Coding RNA Polymorphisms in Cancer Chemotherapeutic Response

2021 ◽  
Vol 11 (6) ◽  
pp. 513
Author(s):  
Zheng Zhang ◽  
Meng Gu ◽  
Zhongze Gu ◽  
Yan-Ru Lou
Keyword(s):  
Molecular Mechanisms ◽  
Neurological Diseases ◽  
Cellular Processes ◽  
Dna And Rna ◽  
Chemotherapeutic Response ◽  
Non Coding Rna ◽  
Response To Chemotherapy ◽  
Personalized Oncology ◽  
Long Non Coding Rna

Genetic polymorphisms are defined as the presence of two or more different alleles in the same locus, with a frequency higher than 1% in the population. Since the discovery of long non-coding RNAs (lncRNAs), which refer to a non-coding RNA with a length of more than 200 nucleotides, their biological roles have been increasingly revealed in recent years. They regulate many cellular processes, from pluripotency to cancer. Interestingly, abnormal expression or dysfunction of lncRNAs is closely related to the occurrence of human diseases, including cancer and degenerative neurological diseases. Particularly, their polymorphisms have been found to be associated with altered drug response and/or drug toxicity in cancer treatment. However, molecular mechanisms are not yet fully elucidated, which are expected to be discovered by detailed studies of RNA–protein, RNA–DNA, and RNA–lipid interactions. In conclusion, lncRNAs polymorphisms may become biomarkers for predicting the response to chemotherapy in cancer patients. Here we review and discuss how gene polymorphisms of lncRNAs affect cancer chemotherapeutic response. This knowledge may pave the way to personalized oncology treatments.

scholarly journals Next Generation Sequencing for the Prediction of the Antibiotic Resistance in Helicobacter pylori: A Literature Review

Antibiotics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 437
Author(s):  
Ilaria Maria Saracino ◽  
Matteo Pavoni ◽  
Angelo Zullo ◽  
Giulia Fiorini ◽  
Tiziana Lazzarotto ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Next Generation Sequencing ◽  
Literature Review ◽  
Molecular Mechanisms ◽  
World Health ◽  
Next Generation ◽  
Culture Methods ◽  
Phenotypic Resistance ◽  
H Pylori ◽  
Generation Sequencing

Background and aims: Only a few antimicrobials are effective against H. pylori, and antibiotic resistance is an increasing problem for eradication therapies. In 2017, the World Health Organization categorized clarithromycin resistant H. pylori as a “high-priority” bacterium. Standard antimicrobial susceptibility testing can be used to prescribe appropriate therapies but is currently recommended only after the second therapeutic failure. H. pylori is, in fact, a “fastidious” microorganism; culture methods are time-consuming and technically challenging. The advent of molecular biology techniques has enabled the identification of molecular mechanisms underlying the observed phenotypic resistance to antibiotics in H. pylori. The aim of this literature review is to summarize the results of original articles published in the last ten years, regarding the use of Next Generation Sequencing, in particular of the whole genome, to predict the antibiotic resistance in H. pylori.Methods: a literature research was made on PubMed. The research was focused on II and III generation sequencing of the whole H. pylori genome. Results: Next Generation Sequencing enabled the detection of novel, rare and complex resistance mechanisms. The prediction of resistance to clarithromycin, levofloxacin and amoxicillin is accurate; for other antimicrobials, such as metronidazole, rifabutin and tetracycline, potential genetic determinants of the resistant status need further investigation.

scholarly journals DEAD-box helicases modulate dicing body formation in Arabidopsis

2021 ◽  
Vol 7 (18) ◽  
pp. eabc6266
Author(s):  
Qi Li ◽  
Ningkun Liu ◽  
Qing Liu ◽  
Xingguo Zheng ◽  
Lu Lu ◽  
...  
Keyword(s):  
Molecular Mechanisms ◽  
Turnip Mosaic Virus ◽  
Liquid Droplets ◽  
Phase Separations ◽  
Body Formation ◽  
Cellular Processes ◽  
Dead Box ◽  
Body Components ◽  
Liquid Phase Separations ◽  
Spatiotemporal Control

Eukaryotic cells contain numerous membraneless organelles that are made from liquid droplets of proteins and nucleic acids and that provide spatiotemporal control of various cellular processes. However, the molecular mechanisms underlying the formation and rapid stress-induced alterations of these organelles are relatively uncharacterized. Here, we investigated the roles of DEAD-box helicases in the formation and alteration of membraneless nuclear dicing bodies (D-bodies) in Arabidopsis thaliana. We uncovered that RNA helicase 6 (RH6), RH8, and RH12 are previously unidentified D-body components. These helicases interact with and promote the phase separation of SERRATE, a key component of D-bodies, and drive the formation of D-bodies through liquid-liquid phase separations (LLPSs). The accumulation of these helicases in the nuclei decreases upon Turnip mosaic virus infections, which couples with the decrease of D-bodies. Our results thus reveal the key roles of RH6, RH8, and RH12 in modulating D-body formation via LLPSs.

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