Multimodal single-cell analysis of nonrandom heteroplasmy distribution in human retinal mitochondrial disease

Mitochondrial retinopathies and optic neuropathies: The impact of retinal imaging on modern understanding of pathogenesis, diagnosis, and management

Advancements in ocular imaging have significantly broadened our comprehension of mitochondrial retinopathies and optic neuropathies by examining the structural and pathological aspects of the retina and optic nerve in these conditions. This article aims to review the prominent imaging characteristics associated with mitochondrial retinopathies and optic neuropathies, aiming to deepen our insight into their pathogenesis and clinical features. Preceding this exploration, the article provides a detailed overview of the crucial genetic and clinical features, which is essential for the proper interpretation of in vivo imaging. More importantly, we will provide a critical analysis on how these imaging modalities could serve as biomarkers for characterization and monitoring, as well as in guiding treatment decisions. However, these imaging methods have limitations, which will be discussed along with potential strategies to mitigate them. Lastly, the article will emphasize the potential advantages and future integration of imaging techniques in evaluating patients with mitochondrial eye disorders, considering the prospects of emerging gene therapies.

A highly reproducible and efficient method for retinal organoid differentiation from human pluripotent stem cells

Human pluripotent stem cell (hPSC)-derived retinal organoids are three-dimensional cellular aggregates that differentiate and self-organize to closely mimic the spatial and temporal patterning of the developing human retina. Retinal organoid models serve as reliable tools for studying human retinogenesis, yet limitations in the efficiency and reproducibility of current retinal organoid differentiation protocols have reduced the use of these models for more high-throughput applications such as disease modeling and drug screening. To address these shortcomings, the current study aimed to standardize prior differentiation protocols to yield a highly reproducible and efficient method for generating retinal organoids. Results demonstrated that through regulation of organoid size and shape using quick reaggregation methods, retinal organoids were highly reproducible compared to more traditional methods. Additionally, the timed activation of BMP signaling within developing cells generated pure populations of retinal organoids at 100% efficiency from multiple widely used cell lines, with the default forebrain fate resulting from the inhibition of BMP signaling. Furthermore, given the ability to direct retinal or forebrain fates at complete purity, mRNA-seq analyses were then utilized to identify some of the earliest transcriptional changes that occur during the specification of these two lineages from a common progenitor. These improved methods also yielded retinal organoids with expedited differentiation timelines when compared to traditional methods. Taken together, the results of this study demonstrate the development of a highly reproducible and minimally variable method for generating retinal organoids suitable for analyzing the earliest stages of human retinal cell fate specification.

Approaches and challenges in identifying, quantifying, and manipulating dynamic mitochondrial genome variations

Mitochondria, the cellular powerhouses, possess their own unique genetic system, including replication, transcription, and translation. Studying these processes is crucial for comprehending mitochondrial disorders, energy production, and their related diseases. Over the past decades, various approaches have been applied in detecting and quantifying mitochondrial genome variations with also the purpose of manipulation of mitochondria or mitochondrial genome for therapeutics. Understanding the scope and limitations of above strategies is not only fundamental to the understanding of basic biology but also critical for exploring disease-related novel target(s), as well to develop innovative therapies. Here, this review provides an overview of different tools and techniques for accurate mitochondrial genome variations identification, quantification, and discuss novel strategies for the manipulation of mitochondria to develop innovative therapeutic interventions, through combining the insights gained from the study of mitochondrial genetics with ongoing single cell omics combined with advanced single molecular tools.

Bibliometric and visual analysis of single-cell sequencing from 2010 to 2022

Background: Single-cell sequencing (SCS) is a technique used to analyze the genome, transcriptome, epigenome, and other genetic data at the level of a single cell. The procedure is commonly utilized in multiple fields, including neurobiology, immunology, and microbiology, and has emerged as a key focus of life science research. However, a thorough and impartial analysis of the existing state and trends of SCS-related research is lacking. The current study aimed to map the development trends of studies on SCS during the years 2010-2022 through bibliometric software. Methods: Pertinent papers on SCS from 2010 to 2022 were obtained using the Web of Science Core Collection. Research categories, nations/institutions, authors/co-cited authors, journals/co-cited journals, co-cited references, and keywords were analyzed using VOSviewer, the R package "bibliometric", and CiteSpace. Results: The bibliometric analysis included 9,929 papers published between 2010 and 2022, and showed a consistent increase in the quantity of papers each year. The United States was the source of the highest quantity of articles and citations in this field. The majority of articles were published in the periodical Nature Communications. Butler A was the most frequently quoted author on this topic, and his article "Integrating single-cell transcriptome data across diverse conditions, technologies, and species" has received numerous citations to date. The literature and keyword analysis showed that studies involving single-cell RNA sequencing (scRNA-seq) were prominent in this discipline during the study period. Conclusion: This study utilized bibliometric techniques to visualize research in SCS-related domains, which facilitated the identification of emerging patterns and future directions in the field. Current hot topics in SCS research include COVID-19, tumor microenvironment, scRNA-seq, and neuroscience. Our results are significant for scholars seeking to identify key issues and generate new research ideas.