Using single‐cell genomics to understand developmental processes and cell fate decisions

High‐throughput ‐omics techniques have revolutionised biology, allowing for thorough and unbiased characterisation of the molecular states of biological systems. However, cellular decision‐making is inherently a unicellular process to which “bulk” ‐omics techniques are poorly suited, as they capture ensemble averages of cell states. Recently developed single‐cell methods bridge this gap, allowing high‐throughput molecular surveys of individual cells. In this review, we cover core concepts of analysis of single‐cell gene expression data and highlight areas of developmental biology where single‐cell techniques have made important contributions. These include understanding of cell‐to‐cell heterogeneity, the tracing of differentiation pathways, quantification of gene expression from specific alleles, and the future directions of cell lineage tracing and spatial gene expression analysis.     

Environmental DNA metabarcoding: Transforming how we survey animal and plant communities

The genomic revolution has fundamentally changed how we survey biodiversity on earth. High‐throughput sequencing (“HTS”) platforms now enable the rapid sequencing of DNA from diverse kinds of environmental samples (termed “environmental DNA” or “eDNA”). Coupling HTS with our ability to associate sequences from eDNA with a taxonomic name is called “eDNA metabarcoding” and offers a powerful molecular tool capable of noninvasively surveying species richness from many ecosystems. Here, we review the use of eDNA metabarcoding for surveying animal and plant richness, and the challenges in using eDNA approaches to estimate relative abundance. We highlight eDNA applications in freshwater, marine and terrestrial environments, and in this broad context, we distill what is known about the ability of different eDNA sample types to approximate richness in space and across time. We provide guiding questions for study design and discuss the eDNA metabarcoding workflow with a focus on primers and library preparation methods. We additionally discuss important criteria for consideration of bioinformatic filtering of data sets, with recommendations for increasing transparency. Finally, looking to the future, we discuss emerging applications of eDNA metabarcoding in ecology, conservation, invasion biology, biomonitoring, and how eDNA metabarcoding can empower citizen science and biodiversity education.     

基因组尺度分析和代谢工程策略

代谢工程是近年来发展起来的新技术,随着各种组学技术的发展,高通量数据整合方法用于分析细胞的代谢网络,改造代谢途径,以提高目标产物的产量。本文就代谢工程的发展状况,基因组尺度的分析技术,以及代谢工程策略进行了综述。分析了生物信息学和系统生物学方法在代谢途径构建和代谢网络分析中的作用,并就存在的问题和可能的解决途径进行了阐述。     

Molecular interaction networks for the analysis of human disease: Utility,limitations, and considerations

High‐throughput ‘‐omics’ data can be combined with large‐scale molecular interaction networks, for example, protein–protein interaction networks, to provide a unique framework for the investigation of human molecular biology. Interest in these integrative ‘‐omics’ methods is growing rapidly because of their potential to understand complexity and association with disease; such approaches have a focus on associations between phenotype and “network‐type.” The potential of this research is enticing, yet there remain a series of important considerations. Here, we discuss interaction data selection, data quality, the relative merits of using data from large high‐throughput studies versus a meta‐database of smaller literature‐curated studies, and possible issues of sociological or inspection bias in interaction data. Other work underway, especially international consortia to establish data formats, quality standards and address data redundancy, and the improvements these efforts are making to the field, is also evaluated. We present options for researchers intending to use large‐scale molecular interaction networks as a functional context for protein or gene expression data, including microRNAs, especially in the context of human disease.     

Advances in Fasciola hepatica research using ‘omics’ technologies

The liver fluke Fasciola hepatica is an economically important pathogen of livestock worldwide, as well as being an important neglected zoonosis. Parasite control is reliant on the use of drugs, particularly triclabendazole, which is effective against multiple parasite stages. However, the spread of parasites resistant to triclabendazole has intensified the pursuit for novel control strategies. Emerging 'omics' technologies are helping advance our understanding of liver fluke biology, specifically the molecules that act at the host-parasite interface and are central to infection, virulence and long-term survival within the definitive host. This review discusses the technological sequencing advances that have facilitated the unbiased analysis of liver fluke biology, resulting in an extensive range of ‘omics’ datasets. In addition, we highlight the ‘omics’ studies of host responses to F. hepatica infection that, when combined with the parasite datasets, provide the opportunity for integrated analyses of host-parasite interactions. These extensive datasets will form the foundation for future in-depth analysis of F. hepatica biology and development, and the search for new drug or vaccine interventions.     

Agreement between amoA Gene-Specific Quantitative PCR and Fluorescence In Situ Hybridization in the Measurement of Ammonia-Oxidizing Bacteria in Activated Sludge

Microbial abundance is central to most investigations in microbial ecology, and its accurate measurement is a challenging task that has been significantly facilitated by the advent of molecular techniques over the last 20 years. Fluorescence in situ hybridization (FISH) is considered the gold standard of quantification techniques; however, it is expensive and offers low sample throughput, both of which limit its wider application. Quantitative PCR (qPCR) is an alternative that offers significantly higher throughput, and it is used extensively in molecular biology. The accuracy of qPCR can be compromised by biases in the DNA extraction and amplification steps. In this study, we compared the accuracy of these two established quantification techniques to measure the abundance of a key functional group in biological wastewater treatment systems, the ammonia-oxidizing bacteria (AOB), in samples from a time-series experiment monitoring a set of laboratory-scale reactors and a full-scale plant. For the qPCR analysis, we tested two different sets of AOB-specific primers, one targeting the 16SrRNA gene and one targeting the ammonia monooxygenase (amoA) gene. We found that there was a positive linear logarithmic relationship between FISH and the amoA gene-specific qPCR, where the data obtained from both techniques was equivalent at the order of magnitude level. The 16S rRNA gene-specific qPCR assay consistently underestimated AOB numbers.     

The proximate/ultimate distinction in the multiple careers of Ernst Mayr

Ernst Mayr's distinction between “ultimate” and “proximate” causes is justly considered a major contribution to philosophy of biology. But how did Mayr come to this “philosophical” distinction, and what role did it play in his earlier “scientific” work? I address these issues by dividing Mayr's work into three careers or phases: 1) Mayr the naturalist/researcher, 2) Mayr the representative of and spokesman for evolutionary biology and systematics, and more recently 3) Mayr the historian and philosopher of biology. If we want to understand the role of the proximate/ultimate distinction in Mayr's more recent career as a philosopher and historian, then it helps to consider hisearlier use of the distinction, in the course of his research, and in his promotion of the professions of evolutionary biology and systematics. I believe that this approach would also shed light on some other important “philosophical” positions that Mayr has defended, including the distinction between “essentialism: and “population thinking.”     

The Biotechnology Facility for International Space Station

The primary mission of the Cellular Biotechnology Program is to advance microgravity as a tool in basic and applied cell biology. The microgravity environment can be used to study fundamental principles of cell biology and to achieve specific applications such as tissue engineering. The Biotechnology Facility (BTF) will provide a state-of-the-art facility to perform cellular biotechnology research onboard the International Space Station (ISS). The BTF will support continuous operation, which will allow performance of long-duration experiments and will significantly increase the on-orbit science throughput.     

The Ship as Laboratory: Making Space for Field Science at Sea

Expanding upon the model of vessels of exploration as scientific instruments first proposed by Richard Sorrenson, this essay examines the changing nature of the ship as scientific space on expedition vessels during the late nineteenth century. Particular attention is paid to the expedition of H.M.S. Challenger (1872–1876) as a turning point in the design of shipboard spaces that established a place for scientists at sea and gave scientific legitimacy to the new science of oceanography. There was a progressive development in research vessel design from “ship as instrument” to “ship as laboratory” and changing spatial practices aboard these vessels were paralleled by changes in shipboard culture. I suggest that the “ship as laboratory” has now in turn been supplanted by a new model, the “ship as invisible technician”, as oceanographic research vessels deploy remote-sensing equipment and gather data that are no longer analyzed on board.     

From cancer big data to treatment: Artificial intelligence in cancer research

In recent years, developing the idea of “cancer big data” has emerged as a result of the significant expansion of various fields such as clinical research, genomics, proteomics and public health records. Advances in omics technologies are making a significant contribution to cancer big data in biomedicine and disease diagnosis. The increasingly availability of extensive cancer big data has set the stage for the development of multimodal artificial intelligence (AI) frameworks. These frameworks aim to analyze high-dimensional multi-omics data, extracting meaningful information that is challenging to obtain manually. Although interpretability and data quality remain critical challenges, these methods hold great promise for advancing our understanding of cancer biology and improving patient care and clinical outcomes. Here, we provide an overview of cancer big data and explore the applications of both traditional machine learning and deep learning approaches in cancer genomic and proteomic studies. We briefly discuss the challenges and potential of AI techniques in the integrated analysis of omics data, as well as the future direction of personalized treatment options in cancer.     

Structural comparison of purified dynein proteins with in situ dynein arms

Using the quick-freeze deep-etch technique, we describe the structure of outer-arm dynein proteins from Chlamydomonas and Tetrahymena after adsorption to a mica surface, after high-salt dissociation, and after glutaraldehyde fixation, and compare these images to the configuration of outer arms bound to microtubules. After adsorption to mica, the extracted dyneins from both organisms look like three-headed “bouquets”, as reported for Tetrahymena by Johnson & Wall (1983b). High magnification images demonstrate that each head carries a slender “stalk” and a long “stem”, and that small subunits decorate the stems and create a “flowerpot” domain at the base of the bouquet. Exposure to high salt induces this trimer to dissociate into a two-headed species and a single-headed species; it also stimulates the decorative elements to dissociate from the stems. Dynein is thus constructed on the same general plan as myosin, with large globular heads, narrow stems and additional small subunits that associate with the stems. The splayed-out image of the bouquet appears to be a distortion arising during adsorption to mica since, after brief glutaraldehyde fixation, the three heads remain closely associated as vertices of a triangular unit. In situ, the three heads also adopt this trigonal configuration. Two of the three are visible from the exterior of the axoneme and constitute the bilobed rigor head we described previously (Goodenough & Heuser, 1982). The third head faces the interior of the axoneme where, we propose, it forms the “hook” of the outer arm as seen in thin section. We further propose that the decorative elements associated with the stem coalesce to form the two outer-arm “feet” seen in situ, and that at least one of the in vitro stalks is equivalent to the in situ stalk, which extends from the head to the B microtubule. Deep-etch images of stretched axonemes, partially extracted axonemes, and dynein-decorated brain microtubules indicate that each outer arm, as traditionally viewed, is a hybrid of two dynein molecules: its two feet derive from one molecule, whereas its trigonal head derives from the molecule located distally. The resultant overlapping configuration creates the diagonal “linkers” seen in situ, which correspond to the in vitro stems. Thus, a row of dynein arms is essentially a dynein polymer that extends from the tip to the base of a doublet microtubule, each head riding on its neighbor's feet like a row of circus elephants. Such dynein-dynein interactions may account for the co-operativity of dynein-microtubule binding, and may play an important role in generating ciliary motility.     

Catalytic RNA,ribozyme, and its applications in synthetic biology

Ribozymes are functional RNA molecules that can catalyze biochemical reactions. Since the discovery of the first catalytic RNA, various functional ribozymes (e.g., self-cleaving ribozymes, splicing ribozymes, RNase P, etc.) have been uncovered, and their structures and mechanisms have been identified. Ribozymes have the advantage of possessing features of “RNA” molecules; hence, they are highly applicable for manipulating various biological systems. To fully employ ribozymes in a broad range of biological applications in synthetic biology, a variety of ribozymes have been developed and engineered. Here, we summarize the main features of ribozymes and the methods used for engineering their functions. We also describe the past and recent efforts towards exploiting ribozymes for effective and novel applications in synthetic biology. Based on studies on their significance in biological applications till date, ribozymes are expected to advance technologies in artificial biological systems.     

The emergence of molecular profiling and omics techniques in seagrass biology; furthering our understanding of seagrasses

Seagrass meadows are disappearing at alarming rates as a result of increasing coastal development and climate change. The emergence of omics and molecular profiling techniques in seagrass research is timely, providing a new opportunity to address such global issues. Whilst these applications have transformed terrestrial plant research, they have only emerged in seagrass research within the past decade; In this time frame we have observed a significant increase in the number of publications in this nascent field, and as of this year the first genome of a seagrass species has been sequenced. In this review, we focus on the development of omics and molecular profiling and the utilization of molecular markers in the field of seagrass biology. We highlight the advances, merits and pitfalls associated with such technology, and importantly we identify and address the knowledge gaps, which to this day prevent us from understanding seagrasses in a holistic manner. By utilizing the powers of omics and molecular profiling technologies in integrated strategies, we will gain a better understanding of how these unique plants function at the molecular level and how they respond to on-going disturbance and climate change events.