Biological Research Research Articles

3D manipulation of small multicellular organisms in soft microtubes

Small multicellular organisms, such as C. elegans and zebrafish larvae, are essential models in biological research, but their 3D manipulation poses challenges due to their small size. Manual positioning is labor-intensive and imprecise. To address this, we developed a soft PDMS microtube that can be gently stretched and released, immobilizing organisms without anesthetization and damage. This tube enables easy rotation and adjustment of orientation, facilitating comprehensive imaging. Functionality testing showed effective immobilization as well as precise imaging and microinjection. Zebrafish larvae were successfully injected with fluorescein in the hindbrain without anesthesia. This technique offers a simple, efficient, and non-damaging method for 3D manipulation and imaging of small multicellular organisms and provides a versatile tool for biological research practices.

Unlocking the Cervix: Biological Mechanisms and Research Gaps in Preterm Birth

Unlocking the Cervix: Biological Mechanisms and Research Gaps in Preterm Birth

The benefits and potential of pre-emptive weed biological control: Three case studies in Queensland, Australia

Invasive weed species can have significant impacts on agriculture, biodiversity and livelihoods. The cost and feasibility of managing these species using conventional means can be prohibitive depending on the size of the infestations or the habitats in which they invade. Under these conditions, biological control is seen as a viable, sustainable means to manage many weeds. However, biological control can take many years and at considerable cost to achieve the desired level of control, due to the numerous steps that are involved, including native range surveys and host-specificity testing of potential agents. Pre-emptive biological control targeting particularly high-risk species prior to their arrival in a country or emerging weeds can be cost-effective, especially if the respective biological control agents have been utilized in other countries. While pre-emptive biological control of arthropods has been investigated previously, there are few examples of pre-emptive biological control of weed species. The invasive weed species, Chromolaena odorata, Mikania micrantha and Coccinia grandis have all been or are currently targets of pre-emptive biological control in Australia. Research on the gall fly Cecidochares connexa was initiated prior to its host, C. odorata being detected in Australia. Cecidochares connexa was eventually released in Australia to control C. odorata, after initial research on the agent found it to be suitably host specific and effective against the target weed. Cecidochares connexa has also been released in numerous other countries in Africa, Asia and the Pacific, where it is providing very good control. Australia funded research on the rust Puccinia spegazzinii as part of a project involving Fiji and Papua New Guinea while the target weed, M. micrantha was a target for eradication in Queensland. The rust was later approved for release in Australia to control M. micrantha following additional host-specificity testing. However, research funded by Australia overseas suggests that the rust may not be able to suppress M. micrantha populations below current levels. Consequently, while P. spegazzinii has been released in numerous countries now, it has not yet been field released in Australia. Biological control research in Australia on C. grandis is relatively new as the weed is relatively minor and not yet declared a target for biological control. Consequently, no biological control agents have yet been released in the country. Pre-emptive biological control of C. odorata and M. micrantha has been particularly cost-effective, not just for Australia, but subsequently for numerous other countries where these weeds were well-established and problematic and the respective biological control agents were later released.

Characterising developmental dynamics of adult epigenetic clock sites

DNA methylation (DNAm), an epigenetic mechanism that regulates gene activity in response to genetic and environmental influences, changes as we age. DNAm at specific sites on the genome can be used to calculate 'epigenetic clocks', which are powerful biomarkers of age, as well as of ageing. However, little is known about how these clock sites 'behave' during development and what factors influence their variability in early life. This knowledge could be used to optimise healthy ageing well before the onset of age-related conditions. We leveraged results from two longitudinal population-based cohorts (N=5019 samples from 2348 individuals) to characterise trajectories of adult clock sites from birth to early adulthood. To explore what factors may drive early individual differences at these clock sites, we also tested for enrichment of genetic factors and prenatal exposures based on existing epigenome-wide association meta-analyses. We find that clock sites (i) diverge widely in their developmental trajectories, often showing non-linear change over time; (ii) are substantially more likely than non-clock sites to vary between individuals already from birth, differences that are predictive of DNAm variation at later ages; and (iii) show enrichment for genetic influences and prenatal environmental exposures, including prenatal smoking, diet and maternal physical health conditions. These results suggests that age(ing)-related epigenetic processes might originate-and differ between individuals-already very early in development. Understanding what drives these differences may in future help us to devise better strategies to promote healthy ageing. This research was conducted while C.A.M.C. was a Hevolution/AFAR New Investigator Awardee in Aging Biology and Geroscience Research. Full personal funding details, as well as cohort funding details, can be found in the Acknowledgements.

Microfluidic device-assisted 3D cell spheroids isolation, staining and embedding

3D cell spheroids have emerged as indispensable tools in cell biology research. In this study, the efficacy of an open-close switchable microfluidic device for on-chip staining and agar-embedding of 3D spheroids was thoroughly validated, especially in preparation for immunohistochemistry (IHC) analysis. The on-chip staining procedure, employing Trypan blue and Calcein-AM/PI staining, was demonstrated to evaluate the cell viability of spheroids. During overextended culture periods, a discernible decline in cell viability was observed at the central region of the spheroids, offering valuable information on the temporal aspects of spheroid development. On-chip agar embedding stands out for its precise control over the location and orientation of three-dimensional spheroids, a key factor in exploring cellular architecture, especially in fused spheroids using IHC analysis. In comparison to tube-based staining, this method significantly cuts down on reagent use and analysis time. This not only boosts efficiency but also lowers the risk of spheroid damage or loss during staining, highlighting its potential for handling miniaturized tissue samples and biopsies in cell assays. The on-chip staining and agar-embedding techniques presented here not only provide valuable insights into spheroids’ behavior but also pave the way for further developments in miniaturized tissue analysis and cell-based assays.

Design, performance, processing, and validation of a pooled CRISPR perturbation screen for bacterial toxins.

Unbiased forward genetic screens have been extensively employed in biological research to elucidate functional genomics. In pooled clustered regularly interspaced short palindromic repeats (CRISPR) perturbation screens, various genetically encoded gain-of-function or loss-of-function mutations are introduced into a heterogeneous population of cells. Subsequently, these cells are screened for phenotypes, perturbation-associated genotypes are analyzed and a connection between genotype and phenotype is determined. CRISPR screening techniques enable the investigation of important biological questions, such as how bacterial toxins kill cells and cause disease. However, the broad spectrum of effects caused by diverse toxins presents a challenge when selecting appropriate screening strategies. Here, we provide a step-by-step protocol for a genome-wide pooled CRISPR perturbation screen to study bacterial toxins. We describe technical considerations, pilot experiments, library construction, screen execution, result analysis and validation of the top enriched hits. These screens are applicable for many different types of toxins and are anticipated to reveal a repertoire of host factors crucial in the intoxication pathway, such as receptors, trafficking/translocation factors and substrates. The entire protocol takes 21-27 weeks and does not require specialized knowledge beyond basic biology.

High-refractive-index glass device fabricated by room temperature bonding

Abstract Wafer bonding is an essential technology for attaching various materials, including glass. Glass-glass bonding has been applied to fabricate glass micro/nanofluidic devices that work as analytical tools for chemical and biological research. Here, we report the fabrication of micro/nanofluidic devices consisting of a high refractive index (HRI) glass as a component of the device for the first time. Although HRI glass has been used for high-sensitivity and high-resolution imaging in microscopy, it has not been used for glass fluidic devices due to the lack of bonding method for HRI glass. The glass fluidic devices were made through glass-glass bonding at room temperature, which could avoid severe damage to bonded substrates of two glass types due to different rates of thermal expansion. The pressure endurance of these devices was measured to find the correlation with the surface properties of glass substrates. The measured results indicated that chemical groups other than SiOH enhanced the pressure endurance of the devices. Thus, these chemical groups helped to form the fluidic devices consisting of HRI glass and another glass type, borosilicate or fused silica, to achieve practical pressure endurance up to 270 kPa. The HRI glass-incorporating device showed 8-fold higher sensitivity and 30 % narrower spatial resolution of fluorescence signals than the other devices with non-HRI glass.

Seq-Scope: repurposing Illumina sequencing flow cells for high-resolution spatial transcriptomics.

Spatial transcriptomics technologies aim to advance gene expression studies by profiling the entire transcriptome with intact spatial information from a single histological slide. However, the application of spatial transcriptomics is limited by low resolution, limited transcript coverage, complex procedures, poor scalability and high costs of initial setup and/or individual experiments. Seq-Scope repurposes the Illumina sequencing platform for high-resolution, high-content spatial transcriptome analysis, overcoming these limitations. It offers submicrometer resolution, high capture efficiency, rapid turnaround time and precise annotation of histopathology at a much lower cost than commercial alternatives. This protocol details the implementation of Seq-Scope with an Illumina NovaSeq 6000 sequencing flow cell, allowing the profiling of multiple tissue sections in an area of 7 mm × 7 mm or larger. We describe the preparation of a fresh-frozen tissue section for both histological imaging and sequencing library preparation and provide a streamlined computational pipeline with comprehensive instructions to integrate histological and transcriptomic data for high-resolution spatial analysis. This includes the use of conventional software tools for single-cell and spatial analysis, as well as our recently developed segmentation-free method for analyzing spatial data at submicrometer resolution. Aside from array production and sequencing, which can be done in batches, tissue processing, library preparation and running the computational pipeline can be completed within 3 days by researchers with experience in molecular biology, histology and basic Unix skills. Given its adaptability across various biological tissues, Seq-Scope establishes itself as an invaluable tool for researchers in molecular biology and histology.

PhyKIT: A Multitool for Phylogenomics.

Multiple sequence alignments and phylogenetic trees are rich in biological information and are fundamental to research in biology. PhyKIT is a tool for processing and analyzing the information content of multiple sequence alignments and phylogenetic trees. Here, we describe how to use PhyKIT for diverse analyses, including (i) constructing a phylogenomic supermatrix, (ii) detecting errors in orthology inference, (iii) quantifying biases in phylogenomic data sets, (iv) identifying radiation events or lack of resolution using gene support frequencies, and (v) conducting evolution-based screens to facilitate gene function prediction. Several PhyKIT functions that streamline multiple sequence alignment and phylogenetic processing-such as renaming FASTA entries or tree tips-are also discussed. These protocols demonstrate how simple command-line operations in the unified framework of PhyKIT facilitate diverse phylogenomic data analysis and processing, from supermatrix construction and diagnosis to gaining clues about gene function. © 2024 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Installing PhyKIT and syntax for usage Basic Protocol 2: Constructing a phylogenomic supermatrix Basic Protocol 3: Detecting anomalies in orthology relationships Basic Protocol 4: Quantifying biases in phylogenomic data matrices and related measures Basic Protocol 5: Identifying polytomies Basic Protocol 6: Assessing gene-gene coevolution as a genetic screen.

GPT4Kinase: High-accuracy prediction of inhibitor-kinase binding affinity utilizing large language model.

The accurate prediction of inhibitor-kinase binding affinity is crucial in biological research and medical applications. Particularly, kinases play a pivotal role in numerous cellular processes and are essential enzymes in Mitogen-Activated Protein Kinase (MAPK) signaling pathway. This present study harnesses the capabilities of Large Language Models (LLMs), specifically GPT-4, to predict the binding affinity between inhibitors and kinases within the MAPK pathway, including Raf protein kinase (RAF), Mitogen-activated protein kinase kinase (MEK) and Extracellular Signal-Regulated Kinase (ERK). Remarkably, GPT-4 achieved an impressive 87.31 % accuracy in prediction on RAF binding affinity, and 77.00 % accuracy in comprehensive prediction tasks, substantially outperforming existing mainstream methods such as Autodock Vina (21.21 %), BatchDTA (52.00 %) and KIPP (59.60 %). Furthermore, GPT-4 was employed to delineate the features of high-affinity and low-affinity molecules, as well as their contributing functional groups. These contributing groups were subsequently validated through molecular docking. Additionally, to validate the generalizability of the method, we applied it to six other kinases and achieved a maximum accuracy of 83.78 %. Also, we utilized a dataset comprising over 200 kinases, obtaining a high accuracy of 66.20 %. The study showcases the transformative impact of LLMs on molecular binding affinity prediction, with major implications for biological sciences and therapeutic development.

Integrated membranes system for water application in microbiology/molecular biology

An integrated membrane filtration system was developed to make water purity suitable for microbiology/molecular biology research. Water samples were collected from outlets in different buildings of the National Research Center and analyzed for their composition before filtration. An integrated membrane system was developed based on mathematical modeling. Flat sheet membranes were produced, including microfiltration, ultrafiltration, and nanofiltration membranes. The flat sheet membranes were converted to a spiral wound module filter to simulate the local market filters and applied in the integrated membrane system that was designed and installed. The produced water was analyzed and compared to molecular-grade water used in different molecular biology/microbiology applications. Both PCR, agarose gel electrophoresis, bacterial liquid cultures, and viral propagation indicated that treated water using the herein-developed system exhibited comparable performance to the molecular grade water provided with imported reagent kits. So, this research can offer a promising solution for producing high-quality water suitable for sensitive laboratory applications.

Nature's All-in-One: Multitasking Robots Inspired by Dung Beetles.

Dung beetles impressively coordinate their 6 legs to effectively roll large dung balls. They can also roll dung balls varying in the weight on different terrains. The mechanisms underlying how their motor commands are adapted to walk and simultaneously roll balls (multitasking behavior) under different conditions remain unknown. This study unravels the mechanisms of how dung beetles roll dung balls and adapt their leg movements to stably roll balls over different terrains for multitasking robots. A modular neural-based loco-manipulation control inspired by and based on ethological observations of the ball-rolling behavior of dung beetles is synthesized. The proposed neural-based control contains a central pattern generator (CPG) module, a pattern formation network (PFN) module, and a robot orientation control (ROC) module. The integrated control mechanisms can control a dung beetle-like robot (ALPHA) with biomechanical feet to perform adaptive (multitasking) loco-manipulation (walking and ball-rolling) on various terrains (flat and uneven). It can deal with different ball weights (2.0 and 4.6kg) and ball types (soft and rigid). The control mechanisms can serve as guiding principles for solving sensory-motor coordination for multitasking robots. Furthermore, this study contributes to biological research by enhancing the understanding of sensory-motor coordination for adaptive (multitasking) loco-manipulation behavior in animals.

Chromosome-level genome of Osmia excavata (Hymenoptera: Megachilidae) provides insights into low-temperature tolerance of Osmia pollinator.

The solitary bee Osmia excavata (Hymenoptera: Megachilidae) is a key pollinator managed on a large scale. It has been widely used for commercial pollination of fruit trees, vegetables, and other crops with high efficiency in increasing the crop seeding rate, yield, and seed quality in Northern hemisphere. Here, a high-quality chromosome-level genome of O. excavata was generated using PacBio sequencing along with Hi-C technology. The genome size was 207.02Mb, of which 90.25% of assembled sequences were anchored to 16 chromosomes with a contig N50 of 9,485kb. Approximately 186.83Mb, accounting for 27.93% of the genome, was identified as repeat sequences. The genome comprises 12,259 protein-coding genes, 96.24% of which were functionally annotated. Comparative genomics analysis suggested that the common ancestor of O. excavata and Osmia bicornis (Hymenoptera: Megachilidae) lived 8.54 million years ago. Furthermore, cytochrome P450 family might be involved in the responses of O. excavata to low-temperature stress. Taken together, the chromosome-level genome assembly of O. excavata provides in-depth knowledge and will be a helpful resource for the pollination biology research.

Characterizing southeast Greenland fjord surface ice and freshwater flux to support biological applications

Abstract. Southeast Greenland (SEG) is characterized by complex morphology and environmental processes that create dynamic habitats for top marine predators. Active glaciers producing solid-ice discharge, freshwater flux, offshore sea ice transport, and seasonal landfast-ice formation all contribute to a variable, transient environment within SEG fjord systems. Here, we investigate a selection of physical processes in SEG to provide a regional characterization that reveals physical system processes and supports biological research. SEG fjords exhibit high fjord-to-fjord variability regarding bathymetry, size, shape, and glacial setting, influencing some processes more than others. For example, during fall, the timing of offshore sea ice formation near SEG fjords progresses temporally when moving southward across latitudes, while the timing of offshore sea ice disappearance is less dependent on latitude. The rates of annual freshwater flux into fjords, however, are highly variable across SEG, with annual average input values ranging from ∼ 1 × 108 to ∼ 1.25 × 1010 m3 (∼ 0.1–12.5 Gt) for individual fjords. Similarly, the rates of solid-ice discharge in SEG fjords vary widely – partly due to the irregular distribution of active glaciers across the study area (60–70° N). Landfast sea ice, assessed for eight focus fjords, is seasonal and has a spatial distribution highly dependent on individual fjord topography. Conversely, glacial ice is deposited into fjord systems year-round, with the spatial distribution of glacier-derived ice depending on the location of glacier termini. As climate change continues to affect SEG, the evolution of these metrics will vary individually in their response, and next steps should include moving from characterization to system projection. Due to the projected regional ice sheet persistence that will continue to feed glacial ice into fjords, it is possible that SEG could remain a long-term refugium for polar bears and other ice-dependent species on a centennial to millennial scale, demonstrating a need for continued research into the SEG physical environment.

A programmable platform for probing cell migration and proliferation.

The advent of advanced robotic platforms and workflow automation tools has revolutionized the landscape of biological research, offering unprecedented levels of precision, reproducibility, and versatility in experimental design. In this work, we present an automated and modular workflow for exploring cell behavior in two-dimensional culture systems. By integrating the BioAssemblyBot® (BAB) robotic platform and the BioApps™ workflow automater with live-cell fluorescence microscopy, our workflow facilitates execution and analysis of in vitro migration and proliferation assays. Robotic assistance and automation allow for the precise and reproducible creation of highly customizable cell-free zones (CFZs), or wounds, in cell monolayers and "hands-free," schedulable integration with real-time monitoring systems for cellular dynamics. CFZs are designed as computer-aided design models and recreated in confluent cell layers by the BAB 3D-Bioprinting tool. The dynamics of migration and proliferation are evaluated in individual cells using live-cell fluorescence microscopy and an in-house pipeline for image processing and single-cell tracking. Our robotics-assisted approach outperforms manual scratch assays with enhanced reproducibility, adaptability, and precision. The incorporation of automation further facilitates increased flexibility in wound geometry and allows for many experimental conditions to be analyzed in parallel. Unlike traditional cell migration assays, our workflow offers an adjustable platform that can be tailored to a wide range of applications with high-throughput capability. The key features of this system, including its scalability, versatility, and the ability to maintain a high degree of experimental control, position it as a valuable tool for researchers across various disciplines.

How do Large Language Models understand Genes and Cells

Researching genes and their interactions is crucial for deciphering the fundamental laws of cellular activity, advancing disease treatment, drug discovery, and more. Large language Models (LLMs), with their profound text comprehension and generation capabilities, have made significant strides across various natural science fields. However, their application in cell biology remains limited and a systematic evaluation of their performance is lacking. To address this gap, in this paper, we select seven mainstream LLMs and evaluate their performance across nine gene-related problem scenarios. Our findings indicate that LLMs possess a certain level of understanding of genes and cells, but still lag behind domain-specific models in comprehending transcriptional expression profiles. Moreover, we have improved the current method of textual representation of cells, enhancing the LLMs’ ability to tackle cell annotation tasks. We encourage cell biology researchers to leverage LLMs for problem-solving while being mindful of the associated challenges. We release our code and data at https://github.com/epang-ucas/Evaluate_LLMs_to_Genes .

3D-printed microfluidic and millifluidic devices for cell culture and mechanotransduction studies: A review

The practice of conventional cell culture techniques affects the quality of biological research in mechanobiology by not replicating the cell’s microenvironment adequately. Microfluidic devices resembling 3D in vivo cell culture offer viable alternatives for mechanobiology studies and other applications including cell screening, cell separation, and point-of-care diagnostics. This review highlights recent advances in additive manufacturing (AM) to fabricate microfluidic and millifluidic devices through fast design iterations and cost reduction compared with conventional device manufacturing. Key advances in AM technologies such as fused deposition modeling (FDM), stereolithography apparatus (SLA), and digital light processing (DLP) have allowed the direct manufacture of complex microfluidic devices with master molds and sacrificial structures using multiple material components. Currently, available 3D printed devices for the precise fabrication of milli- and microfluidic devices, essential to mimicking the cellular microenvironment, while economically reducing production costs by eliminating expensive clean-room environments and reducing material waste are highlighted.

Predicting the Pathway Involvement of All Pathway and Associated Compound Entries Defined in the Kyoto Encyclopedia of Genes and Genomes

Background/Objectives: Predicting the biochemical pathway involvement of a compound could facilitate the interpretation of biological and biomedical research. Prior prediction approaches have largely focused on metabolism, training machine learning models to solely predict based on metabolic pathways. However, there are many other types of pathways in cells and organisms that are of interest to biologists. Methods: While several publications have made use of the metabolites and metabolic pathways available in the Kyoto Encyclopedia of Genes and Genomes (KEGG), we downloaded all the compound entries with pathway annotations available in the KEGG. From these data, we constructed a dataset where each entry contained features representing compounds combined with features representing pathways, followed by a binary label indicating whether the given compound is associated with the given pathway. We trained multi-layer perceptron binary classifiers on variations of this dataset. Results: The models trained on 6485 KEGG compounds and 502 pathways scored an overall mean Matthews correlation coefficient (MCC) performance of 0.847, a median MCC of 0.848, and a standard deviation of 0.0098. Conclusions: This performance on all 502 KEGG pathways represents a roughly 6% improvement over the performance of models trained on only the 184 KEGG metabolic pathways, which had a mean MCC of 0.800 and a standard deviation of 0.021. These results demonstrate the capability to effectively predict biochemical pathways in general, in addition to those specifically related to metabolism. Moreover, the improvement in the performance demonstrates additional transfer learning with the inclusion of non-metabolic pathways.

Biological literacy skills of senior high school student using local potential-based biodiversity question sets

One of the efforts to improve the quality of education in Indonesia is through learning by integrating environmental culture. Environmental culture can be packaged in more meaningful learning through biological literacy. This study aims to assess the biological literacy skills of high school students using local potential-based biodiversity question sets. This study includes research with quantitative descriptive methods that aim to describe the biological literacy skills of high school tenth grade students. Biological literacy research data consists of 4 indicators, namely nominal, conceptual, multidimensional and functional. The number of participants was 60 high school students. The initial stage used expert judgment for content validation which was tested by 3 expert validators. Construct validation was carried out based on data collection with the results of 12 question sets that were declared valid. Data analysis of the percentage of students who answered correctly on biological literacy indicators were all at a high level, namely on nominal indicators of 69.37%, conceptual indicators of 70%, functional indicators of 66.87%, and multidimensional indicators of 70%. It is concluded that the local wisdom-based biodiversity question set can be used to measure students' biological literacy skills in schools.

Conducting Human Biology Research Using Invasive Clinical Samples: Methods, Strengths, and Limitations.

Invasive biological samples collected during clinical care represent a valuable yet underutilized source of information about human biology. However, the challenges of working with clinical personnel and the invasive nature of sample collection in biomedical studies can hinder the acquisition of sufficiently large sample sizes for robust statistical analyses. In addition, the incorporation of demographic data from participants is crucial for ensuring the inclusiveness of representative populations, identifying at-risk groups, and addressing healthcare disparities. Drawing on both research experiences and the existing literature, this article provides recommendations for researchers aiming to undertake efficient and impactful projects involving invasive human samples. The suggested strategies include: (1) establishing productive collaborations with clinicians; (2) optimizing sample quality through meticulous collection and handling procedures; and (3) strategically implementing a retrospective model to capitalize on existing invasive sample repositories. When established, cooperative work between clinical health care workers and biological anthropologists can yield insights into human biology that have the potential to improve human health and wellbeing.