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ABSTRACT Optical density is a proxy of total biomass concentration and is commonly used for measuring the growth of bacterial cultures. However, there is a misconception that exponential optical density growth is equivalent to steady-state population growth. Many cells comprise a culture and individuals can differ from one another. Hallmarks of steady-state population growth are stable frequency distributions of cellular properties over time, something total biomass growth alone cannot quantify. Using single-cell mass sensors paired with optical density measurements, we explore when steady-state population growth prevails in typical batch cultures. We find the average cell mass of Escherichia coli and Vibrio cyclitrophicus growing in several media increases by 0.5–1 orders of magnitude within a few hours of inoculation, and that time-invariant mass distributions are only achieved for short periods when cultures are inoculated with low initial biomass concentrations from overnight cultures. These species achieve an effective steady-state after approximately 2.5–4 total biomass doublings in rich media, which can be decomposed to 1 doubling of cell number and 1.5–3 doublings of average cell mass. We also show that typical batch cultures in rich media depart steady-state early in their growth curves at low cell and biomass concentrations. Achieving steady-state population growth in batch culture is a delicate balancing act, so we provide general guidance for commonly used rich media. Quantifying single-cell mass outside of steady-state population growth is an important first step toward understanding how microbes grow in their natural context, where fluctuations pervade at the scale of individuals. IMPORTANCE Microbiologists have watched clear liquid turn cloudy for over 100 years. While the cloudiness of a culture is proportional to its total biomass, growth rates from optical density measurements are challenging to interpret when cells change size. Many bacteria adjust their size at different steady-state growth rates, but also when shifting between starvation and growth. Optical density cannot disentangle how mass is distributed among cells. Here, we use single-cell mass measurements to demonstrate that a population of cells in batch culture achieves a stable mass distribution for only a short period of time. Achieving steady-state growth in rich medium requires low initial biomass concentrations and enough time for individual cell mass accumulation and cell number increase via cell division to balance out. Steady-state growth is important for reliable cell mass distributions and experimental reproducibility. We discuss how mass variation outside of steady-state can impact physiology, ecology, and evolution experiments.

Transient changes in intracellular pH (pHi) regulate normal cell behaviors, but roles for spatiotemporal pHi dynamics in single-cell behaviors remain unclear. Here, we mapped single-cell spatiotemporal pHi dynamics during mammalian cell cycle progression both with and without cell cycle synchronization. We found that single-cell pHi is dynamic throughout the cell cycle: pHi decreases at G1/S, increases in mid-S, decreases at late S, increases at G2/M and rapidly decreases during mitosis. Importantly, although pHi is highly dynamic in dividing cells, non-dividing cells have attenuated pHi dynamics. Using two independent pHi manipulation methods, we found that low pHi inhibits completion of S phase whereas high pHi promotes both S/G2 and G2/M transitions. Our data also suggest that low pHi cues G1 exit, with decreased pHi shortening G1 and increased pHi elongating G1. Furthermore, dynamic pHi is required for S phase timing, as high pHi elongates S phase and low pHi inhibits S/G2 transition. This work reveals that spatiotemporal pHi dynamics are necessary for cell cycle progression at multiple phase transitions in single human cells. [ABSTRACT FROM AUTHOR]

Purpose of reviewIn this review, we summarize recent developments in single-cell technologies that can be employed for the functional and molecular classification of endocrine cells in normal and neoplastic tissue.Recent findingsThe emergence of new platforms for the isolation, analysis, and dynamic assessment of individual cell identity and reactive behavior enables experimental deconstruction of intratumoral heterogeneity and other contexts where variability in cell signaling and biochemical responsiveness inform biological function and clinical presentation. These tools are particularly appropriate for examining and classifying endocrine neoplasias, as the clinical sequelae of these tumors are often driven by disrupted hormonal responsiveness secondary to compromised cell signaling. Single-cell methods allow for multidimensional experimental designs incorporating both spatial and temporal parameters with the capacity to probe dynamic cell signaling behaviors and kinetic response patterns dependent upon sequential agonist challenge.SummaryIntratumoral heterogeneity in the provenance, composition, and biological activity of different forms of endocrine neoplasia presents a significant challenge for prognostic assessment. Single-cell technologies provide an array of powerful new approaches uniquely well suited for dissecting complex endocrine tumors. Studies examining the relationship between clinical behavior and tumor compositional variations in cellular activity are now possible, providing new opportunities to deconstruct the underlying mechanisms of endocrine neoplasia.

ABSTRACT Some of the protist species which colonize the hindguts of wood-feeding Reticulitermes termites are associated with endosymbiotic bacteria belonging to the genus Endomicrobium. In this study, we focused on the endosymbionts of three protist species from Reticulitermes flavipes, as follows: Pyrsonympha vertens, Trichonympha agilis, and Dinenympha species II. Since these protist hosts represented members of different taxa which colonize separate niches within the hindguts of their termite hosts, we investigated if these differences translated to differential gene content and expression in their endosymbionts. Following assembly and comparative genome and transcriptome analyses, we discovered that these endosymbionts differed with respect to some possible niche-specific traits, such as carbon metabolism. Our analyses suggest that species-specific genes related to carbon metabolism were acquired by horizontal gene transfer (HGT) and may have come from taxa which are common in the termite hind gut. In addition, our analyses suggested that these endosymbionts contain and express genes related to natural transformation (competence) and recombination. Taken together, the presence of genes acquired by HGT and a putative competence pathway suggest that these endosymbionts are not cut off from gene flow and that competence may be a mechanism by which members of Endomicrobium can acquire new traits. IMPORTANCE The composition and structure of wood, which contains cellulose, hemicellulose, and lignin, prevent most organisms from using this common food source. Termites are a rare exception among animals, and they rely on a complex microbiota housed in their hindguts to use wood as a source of food. The lower termite, Reticulitermes flavipes, houses a variety of protists and prokaryotes that are the key players in the disassembly of lignocellulose. Here, we describe the genomes and the gene expression profiles of five Endomicrobium endosymbionts living inside three different protist species from R. flavipes. Data from these genomes suggest that these Endomicrobium species have different mechanisms for using carbon. In addition, they harbor genes that may be used to import DNA from their environment. This process of DNA uptake may contribute to the high levels of horizontal gene transfer noted previously in Endomicrobium species.

The combined approach of incubating environmental samples with stable isotope-labeled substrates followed by single-cell analyses through high-resolution secondary ion mass spectrometry (NanoSIMS) or Raman microspectroscopy provides insights into the in situ function of microorganisms. This approach has found limited application in soils presumably due to the dispersal of microbial cells in a large background of particles. We developed a pipeline for the efficient preparation of cell extracts from soils for subsequent single-cell methods by combining cell detachment with separation of cells and soil particles followed by cell concentration. The procedure was evaluated by examining its influence on cell recoveries and microbial community composition across two soils. This approach generated a cell fraction with considerably reduced soil particle load and of sufficient small size to allow single-cell analysis by NanoSIMS, as shown when detecting active N2-fixing and cellulose-responsive microorganisms via (15)N2 and (13)C-UL-cellulose incubations, respectively. The same procedure was also applicable for Raman microspectroscopic analyses of soil microorganisms, assessed via microcosm incubations with a (13)C-labeled carbon source and deuterium oxide (D2O, a general activity marker). The described sample preparation procedure enables single-cell analysis of soil microorganisms using NanoSIMS and Raman microspectroscopy, but should also facilitate single-cell sorting and sequencing.

Epigenetic regulation as a means for bacterial adaptation is receiving increasing interest in the last decade. Significant efforts have been directed towards understanding the mechanisms giving raise to phenotypic heterogeneity within bacterial populations and its adaptive relevance. Phenotypic heterogeneity mostly refers to phenotypic variation not linked to genetic differences nor to environmental stimuli. Recent findings on the relevance of phenotypic heterogeneity on some bacterial complex traits are causing a shift from traditional assays where bacterial phenotypes are defined by averaging population-level data, to single-cell analysis that focus on bacterial individual behavior within the population. Fluorescent labeling is a key asset for single-cell gene expression analysis using flow cytometry, fluorescence microscopy, and/or microfluidics.We previously described the generation of chromosome-located transcriptional gene fusions to fluorescent reporter genes using the model bacterial plant pathogen Pseudomonas syringae. These fusions allow researchers to follow variation in expression of the gene(s) of interest, without affecting gene function. In this report, we improve the analytic power of the method by combining such transcriptional fusions with constitutively expressed compatible fluorescent reporter genes integrated in a second, neutral locus of the bacterial chromosome. Constitutively expressed fluorescent reporters allow for the detection of all bacteria comprising a heterogeneous population, regardless of the level of expression of the concurrently monitored gene of interest, thus avoiding the traditional use of stains often incompatible with samples from complex contexts such as the leaf., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Importance: Microbiologists have watched clear liquid turn cloudy for over 100 years. While the cloudiness of a culture is proportional to its total biomass, growth rates from optical density measurements are challenging to interpret when cells change size. Many bacteria adjust their size at different steady-state growth rates, but also when shifting between starvation and growth. Optical density cannot disentangle how mass is distributed among cells. Here, we use single-cell mass measurements to demonstrate that a population of cells in batch culture achieves a stable mass distribution for only a short period of time. Achieving steady-state growth in rich medium requires low initial biomass concentrations and enough time for individual cell mass accumulation and cell number increase via cell division to balance out. Steady-state growth is important for reliable cell mass distributions and experimental reproducibility. We discuss how mass variation outside of steady-state can impact physiology, ecology, and evolution experiments., Competing Interests: S.R.M. is a co-founder of Travera and Affinity Biosensors, which develop technologies relevant to the research presented in this work.

Genomic and transcriptional heterogeneity is prevalent among the most common and aggressive primary brain tumors in children and adults. Over the past 20 years, advances in bioengineering, biochemistry and bioinformatics have enabled the development of an array of techniques to study tumor biology at single-cell resolution. The application of these techniques to study primary brain tumors has helped advance our understanding of their intra-tumoral heterogeneity and uncover new insights regarding their co-option of developmental programs and signaling from their microenvironment to promote tumor proliferation and invasion. These insights are currently being harnessed to develop new therapeutic approaches. Here we provide an overview of current single-cell techniques and discuss relevant biology and therapeutic insights uncovered by their application to primary brain tumors in children and adults., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Society for Neuro-Oncology.)

Virtually all biomedical applications of positron emission tomography (PET) use images to represent the distribution of a radiotracer. However, PET is increasingly used in cell tracking applications, for which the “imaging” paradigm may not be optimal. Here, we investigate an alternative approach, which consists in reconstructing the time-varying position of individual radiolabeled cells directly from PET measurements. As a proof of concept, we formulate a new algorithm for reconstructing the trajectory of one single moving cell directly from list-mode PET data. We model the trajectory as a 3-D B-spline function of the temporal variable and use nonlinear optimization to minimize the mean-square distance between the trajectory and the recorded list-mode coincidence events. Using Monte Carlo simulations (GATE), we show that this new algorithm can track a single source moving within a small-animal PET system with <3 mm accuracy provided that the activity of the cell [Bq] is greater than four times its velocity [mm/s]. The algorithm outperforms conventional ML-EM as well as the “minimum distance” method used for positron emission particle tracking (PEPT). The new method was also successfully validated using experimentally acquired PET data. In conclusion, we demonstrated the feasibility of a new method for tracking a single moving cell directly from PET list-mode data, at the whole-body level, for physiologically relevant activities and velocities. [ABSTRACT FROM PUBLISHER]

Physarum polycephalum is a unicellular eukaryote belonging to the amoebozoa group of organisms. The complex life cycle involves various cell types that differ in morphology, function, and biochemical composition. Sporulation, one step in the life cycle, is a stimulus-controlled differentiation response of macroscopic plasmodial cells that develop into fruiting bodies. Well-established Mendelian genetics and the occurrence of macroscopic cells with a naturally synchronous population of nuclei as source of homogeneous cell material for biochemical analyses make Physarum an attractive model organism for studying the regulatory control of cell differentiation. Here, we develop an approach using RNA-sequencing (RNA-seq), without needing to rely on a genome sequence as a reference, for studying the transcriptomic changes during stimulus-triggered commitment to sporulation in individual plasmodial cells. The approach is validated through the obtained expression patterns and annotations, and particularly the results from up- and downregulated genes, which correlate well with previous studies. [ABSTRACT FROM AUTHOR]

Some of the protist species which colonize the hindguts of wood-feeding Reticulitermes termites are associated with endosymbiotic bacteria belonging to the genus Endomicrobium . In this study, we focused on the endosymbionts of three protist species from Reticulitermes flavipes, as follows: Pyrsonympha vertens, Trichonympha agilis, and Dinenympha species II. Since these protist hosts represented members of different taxa which colonize separate niches within the hindguts of their termite hosts, we investigated if these differences translated to differential gene content and expression in their endosymbionts. Following assembly and comparative genome and transcriptome analyses, we discovered that these endosymbionts differed with respect to some possible niche-specific traits, such as carbon metabolism. Our analyses suggest that species-specific genes related to carbon metabolism were acquired by horizontal gene transfer (HGT) and may have come from taxa which are common in the termite hind gut. In addition, our analyses suggested that these endosymbionts contain and express genes related to natural transformation (competence) and recombination. Taken together, the presence of genes acquired by HGT and a putative competence pathway suggest that these endosymbionts are not cut off from gene flow and that competence may be a mechanism by which members of Endomicrobium can acquire new traits. IMPORTANCE The composition and structure of wood, which contains cellulose, hemicellulose, and lignin, prevent most organisms from using this common food source. Termites are a rare exception among animals, and they rely on a complex microbiota housed in their hindguts to use wood as a source of food. The lower termite, Reticulitermes flavipes, houses a variety of protists and prokaryotes that are the key players in the disassembly of lignocellulose. Here, we describe the genomes and the gene expression profiles of five Endomicrobium endosymbionts living inside three different protist species from R. flavipes . Data from these genomes suggest that these Endomicrobium species have different mechanisms for using carbon. In addition, they harbor genes that may be used to import DNA from their environment. This process of DNA uptake may contribute to the high levels of horizontal gene transfer noted previously in Endomicrobium species.

Single-cell sequencing methods provide the highest resolution insight into cellular heterogeneity. Owing to their rapid growth and decreasing cost, they are now widely accessible to scientists worldwide. Single-cell technologies enable analysis of a large number of cells, making them powerful tools to characterise rare cell types and refine our understanding of diverse cell states. Moreover, single-cell application in biomedical sciences helps to unravel mechanisms related to disease pathogenesis and outcome. In this Viewpoint, we briefly describe existing single-cell methods (genomics, transcriptomics, epigenomics, proteomics, and mulitomics), comment on available analysis tools, and give examples of method applications in the biomedical field., (© 2021 The Authors. Journal of Cellular Biochemistry Published by Wiley Periodicals LLC.)

Methylation of RNA is normally monitored in purified cell lysates using next-generation sequencing, gel electrophoresis, or mass spectrometry as readouts. These bulk methods require the RNA from ~10 4 to 10 7 cells to be pooled to generate sufficient material for analysis. Here we describe a method-methylation-sensitive RNA in situ hybridization (MR-FISH)-that assays rRNA methylation in bacteria on a cell-by-cell basis, using methylation-sensitive hybridization probes and fluorescence microscopy. We outline step-by-step protocols for designing probes, in situ hybridization, and analysis of data using freely available code.

The last decade has seen significant effort directed toward the role of phenotypic heterogeneity in bacterial adaptation. Phenotypic heterogeneity usually refers to phenotypic diversity that takes place through nongenetic means, independently of environmental induced variation. Recent findings are changing how microbiologists analyze bacterial behavior, with a shift from traditional assays averaging large populations to single-cell analysis focusing on bacterial individual behavior. Fluorescence-based methods are often used to analyze single-cell gene expression by flow cytometry, fluorescence microscopy and/or microfluidics. Moreover, fluorescence reporters can also be used to establish where and when are the genes of interest expressed. In this chapter, we use the model bacterial plant pathogen Pseudomonas syringae to illustrate a method to generate chromosome-located transcriptional gene fusions to fluorescent reporter genes, without affecting the function of the gene of interest.