Life Science Research Research Articles

How to introduce a new bacteriophage on the block: a short guide to phage classification.

Bacteriophage (phage) studies established the field of molecular biology and continue to propel life science research forward due to their diversity, abundance, and potential applications. In this Gem article, we orient newcomers to four common ways phages are currently classified: infection cycle, morphology, taxonomy, and supergroup. By using these classifications, researchers can determine where any novel phage fits into the scheme of the known "phage-verse".

Machine learning in microscopy - insights, opportunities and challenges.

Machine learning (ML) is transforming the field of image processing and analysis, from automation of laborious tasks to open-ended exploration of visual patterns. This has striking implications for image-driven life science research, particularly microscopy. In this Review, we focus on the opportunities and challenges associated with applying ML-based pipelines for microscopy datasets from a user point of view. We investigate the significance of different data characteristics - quantity, transferability and content - and how this determines which ML model(s) to use, as well as their output(s). Within the context of cell biological questions and applications, we further discuss ML utility range, namely data curation, exploration, prediction and explanation, and what they entail and translate to in the context of microscopy. Finally, we explore the challenges, common artefacts and risks associated with ML in microscopy. Building on insights from other fields, we propose how these pitfalls might be mitigated for in microscopy.

Development of Beam Irradiation System for Life Science Research at RAON

Development of Beam Irradiation System for Life Science Research at RAON

(Pre)Clinical Metabolomics Analysis.

Metabolomics is the scientific field with the eager goal to comprehensively analyze the entirety of all small molecules of a biological system, i.e., the metabolome. Over the last few years, metabolomics has matured to become an analytical cornerstone of life science research across diverse fields, from fundamental biochemical applications to preclinical studies, including biomarker discovery and drug development. In this chapter, we provide an introduction to (pre)clinical metabolomics. We define key metabolomics aspects and provide the basis to thoroughly understand the relevance of this field in a biological and clinical context. We present and explain state-of-the-art analytical technologies devoted to metabolomic analysis as well as emerging technologies, discussing both strengths and weaknesses. Given the ever-increasing demand for handling complex datasets, the role of bioinformatics approaches in the context of metabolomic analysis is also illustrated.

Recent progresses on space life science research in China

In the past decades, China has made significant progress on space life science research. Since completing the construction of the China Space Station (CSS) at the end of 2022, space life science research in China has entered a new era. Through carrying out numerous experiments on space life sciences, space medicine, and space agriculture conducted aboard the Shenzhou series, the CSS, and ground-based space environment simulation platforms, Chinese scientists have uncovered the effects of the space environment on the physiological and molecular mechanisms of live organisms. These findings provide essential theoretical support for long-term manned space exploration. In this article, we review the new discoveries made by Chinese researchers, focusing on the impacts of both actual and simulated space environment on cells, microorganisms, plants, animals, and human health.

Bio-based polylactic acid labware as a sustainable alternative for microbial cultivation in life science laboratories

Single-use plastics (SUPs) in life science laboratories account for approximately 5.5 million tonnes of waste per year globally. Of SUPs used in life science laboratories, Petri dishes, centrifuge tubes, and inoculation loops are some of the most common. In order to reduce the reliance on petrochemical-based SUPs in the life science research laboratory and minimize the negative environmental impacts associated with SUPs, this research investigates the applicability of polylactic acid (PLA) in single-use labware as a replacement for petrochemical-based plastics. PLA is one of the most well-studied biodegradable plastics that can be produced from sustainable resources. Commercially available PLA was used to 3D print a select range of labware to test the suitability of PLA-based material for routine microbiology work. An injection moulded PLA-based Petri dish was also designed and produced, for increased optical clarity. The biocompatibility was tested against Gram-negative (Escherichia coli) and Gram-positive (Staphylococcus epidermidis) strains of bacteria. The PLA-based labware did not negatively impact the cell growth, viability, and metabolic activity of the bacterial cultures. The injection moulded PLA Petri dish showed a reduced colony forming unit count for the Gram-negative E. coli strain compared to the polystyrene Petri dish, ∼1.5 × 109 CFU/mL and ∼3.0 × 109 CFU/mL respectively, during late-exponential growth. The colony counts were, however, in the same order of magnitude. This observed difference may be due to the internal environment inside the Petri dish, hence the internal O2 concentration, humidity, and temperature during bacterial growth were investigated. This work demonstrates, for the first time, a full successful workflow of bacterial growth using a sustainable bioplastic, providing a pathway to reducing the environmental impacts of SUPs in life science laboratories.

A Self-led Self-management Intervention Supporting Teens with IBD (ASSIST-IBD): protocol for a feasibility study of a novel digital treatment adherence intervention

IntroductionTreatment non-adherence is common in young people with inflammatory bowel disease (IBD), yet support is lacking. A self-led self-management intervention supporting teens with IBD (ASSIST-IBD) is a new theory-based digital...

Accelerating Museum AI Research and Application at the UK Natural History Museum: The NHM AI Lab Programme

The United Kingdom's Natural History Museum (NHM) AI Lab Programme represents a pioneering initiative aimed at harnessing the power of artificial intelligence (AI) to bridge the gap between the museum's extensive collection and cutting-edge AI technologies. Despite its immense potential, the application of AI in museum research remains nascent (e.g., He et al. 2024), with some individual research groups pursuing independent projects without cohesive collaboration with AI experts who know or have experience in similar endeavours. Moreover, differing standards in utilising AI among researchers add complexity to the field. The NHM AI Lab Programme addresses these challenges by co-creating AI pilot projects that bring together the NHM's collection, academic researchers, and AI experts. The NHM AI Lab Programme serves as a nexus for interdisciplinary collaboration, offering expertise in AI, machine learning, data science, and software engineering to support NHM researchers. Through one-to-one consultations and collaborative research projects, the NHM AI Lab Programme facilitates the integration of innovative AI-driven technologies into streamlining digitisation workflows and enhancing Earth and Life Science research at the NHM. In less than a year since its inception, our Programme has achieved several milestones, hosting around 20 diverse projects. These include research projects such as the application of AI for the automatic detection and identification of nannofossils in chalk, the classification of ancient shark and dinosaur teeth, the prediction of mammal disease outbreaks, and the extraction of data from historical bird egg records. Additional projects focus on the automation of mineral analysis and the detection of secondary impact craters on planetary surfaces using AI. Some led to journal publications (e.g., He et al. 2024), while others streamlined NHM researchers' workflows, enhancing their processes of research and digitisation. Moreover, several initiatives have paved the way for new funding streams and collaborative ventures, as well as promising commercial prospects. Certain projects have pioneered the creation or transformation of datasets to meet AI-ready standards, such as data quality, consistency, accessibility, usability, and data governance protocols, helping to embed AI practices into NHM research. This AI Lab Programme can act as a model for other institutions addressing a similar challenge of bridging the gap between AI and their research and collections. This presentation provides insights into the establishment and operation of the NHM AI Lab Programme, shares experiences, highlights successful collaborations, discusses challenges encountered, and outlines future directions.

Effects of single housing on behavior, corticosterone level and body weight in male and female mice

BackgroundExperimental mice are often single-housed either for an individual analysis (feeding behavior, imaging, calorimetry) or as a stress paradigm (social isolation) in translational biomedical research. Reports of the influence of single housing in rodents are conflicting and may depend on age and duration of isolation. Sex is often not included as a factor. In this study we investigated the effects of 4-week single housing in male and female mice on behavior, body weight, and serum corticosterone levels.ResultsBehavioral tests showed no effect on anhedonia and stress coping, anxiety and motor exploration. Social avoidance occurred in both males and females. Regarding physiological effects, single housing did not induce changes in serum corticosterone levels, but reduced body weight gain.ConclusionsWhile some mouse studies of chronic social isolation reported depression-related disturbances, our data suggest that single housing might be not necessarily be too stressful. This is important for animal welfare regulations and experiments in life science research.

Single-molecule detection and super-resolution imaging with a portable and adaptable 3D-printed microscopy platform (Brick-MIC).

Over the past decades, single-molecule and super-resolution microscopy have advanced and represent essential tools for life science research. There is, however, a growing gap between the state of the art and what is accessible to biologists, biochemists, medical researchers, or labs with financial constraints. To bridge this gap, we introduce Brick-MIC, a versatile and affordable open-source 3D-printed microspectroscopy and imaging platform. Brick-MIC enables the integration of various fluorescence imaging techniques with single-molecule resolution within a single platform and exchange between different modalities within minutes. We here present variants of Brick-MIC that facilitate single-molecule fluorescence detection, fluorescence correlation spectroscopy, time-correlated single-photon counting and super-resolution imaging (STORM and PAINT). Detailed descriptions of the hardware and software components, as well as data analysis routines, are provided, to allow non-optics specialists to operate their own Brick-MIC with minimal effort and investments. We foresee that our affordable, flexible, and open-source Brick-MIC platform will be a valuable tool for many laboratories worldwide.

A miniaturized microfluidic nanoplasmonic sensor with cavity reflection enhancement for ultrasensitive molecular interaction analysis

Molecular binding kinetics quantification is pivotal in the design of antibodies, small-molecule drugs, and early diagnosis of complex disease. This study presents a portable microfluidic system, featuring a nanoplasmonic sensor with cavity reflection enhancement (NSCRE), designed for the ultrasensitive detection and analysis of molecular interactions. This device comprises liquid flow paths, generic fiber spectrometers, a versatile NSCRE sensor chip, and a novel data analysis system. Furthermore, a neural network data processing system is developed based on a deep learning model to decrease significant data fluctuations caused by air segments. This “all-in-one” platform, integrating multifunctional, easy-to-use, and renewable NSCRE biosensors, boasts detection capabilities for both slow and rapid kinetics. It can automatically monitor interactions between molecules across a broad range of molecular weights (0.259–150 kDa), allowing for real-time, ultra-sensitive, and highly selective analysis. In addition, the platform with CRE effect facilitates a 7.2-fold increase in reflection intensity signals compared to that of a sensor without CRE. The immunoglobulin G detection with a limit of detection of 73 pM based on this device, showing a 50-fold increase in sensitivity compared to previously reported values. The miniaturized automatic detection system paves a new path for the use of molecular interaction analysis in life science research, drug discovery, early diagnosis, and other fields.

The global geography of artificial intelligence in life science research

Artificial intelligence (AI) promises to transform medicine, but the geographic concentration of AI expertize may hinder its equitable application. We analyze 397,967 AI life science research publications from 2000 to 2022 and 14.5 million associated citations, creating a global atlas that distinguishes productivity (i.e., publications), quality-adjusted productivity (i.e., publications stratified by field-normalized rankings of publishing outlets), and relevance (i.e., citations). While Asia leads in total publications, Northern America and Europe contribute most of the AI research appearing in high-ranking outlets, generating up to 50% more citations than other regions. At the global level, international collaborations produce more impactful research, but have stagnated relative to national research efforts. Our findings suggest that greater integration of global expertize could help AI deliver on its promise and contribute to better global health.

Mammalian genome research resources available from the National BioResource Project in Japan.

Mammalian genome research has conventionally involved mice and rats as model organisms for humans. Given the recent advances in life science research, to understand complex and higher-order biological phenomena and to elucidate pathologies and develop therapies to promote human health and overcome diseases, it is necessary to utilize not only mice and rats but also other bioresources such as standardized genetic materials and appropriate cell lines in order to gain deeper molecular and cellular insights. The Japanese bioresource infrastructure program called the National BioResource Project (NBRP) systematically collects, preserves, controls the quality, and provides bioresources for use in life science research worldwide. In this review, based on information from a database of papers related to NBRP bioresources, we present the bioresources that have proved useful for mammalian genome research, including mice, rats, other animal resources; DNA-related materials; and human/animal cells and microbes.

Machine learning can be as good as maximum likelihood when reconstructing phylogenetic trees and determining the best evolutionary model on four taxon alignments

Phylogenetic tree reconstruction with molecular data is important in many fields of life science research. The gold standard in this discipline is the phylogenetic tree reconstruction based on the Maximum Likelihood method. In this study, we present neural networks to predict the best model of sequence evolution and the correct topology for four sequence alignments of nucleotide or amino acid sequence data. We trained neural networks with different architectures using simulated alignments for a wide range of evolutionary models, model parameters and branch lengths. By comparing the accuracy of model and topology prediction of the trained neural networks with Maximum Likelihood and Neighbour Joining methods, we show that for quartet trees, the neural network classifier outperforms the Neighbour Joining method and is in most cases as good as the Maximum Likelihood method to infer the best model of sequence evolution and the best tree topology. These results are consistent for nucleotide and amino acid sequence data. We also show that our method is superior for model selection than previously published methods based on convolutionary networks. Furthermore, we found that neural network classifiers are much faster than the IQ-TREE implementation of the Maximum Likelihood method. Our results show that neural networks could become a true competitor for the Maximum Likelihood method in phylogenetic reconstructions.

GetGenome: Overcoming inequalities in access to genomics technology.

Although genomics has become integral to life science research, inequitable access to genomics technology remains prevalent. GetGenome, a non-profit organization, aims to overcome this by providing equitable access to genomics technology and training.

Single-Cell Sequencing: High-Resolution Analysis of Cellular Heterogeneity in Autoimmune Diseases.

Autoimmune diseases (AIDs) are complex in etiology and diverse in classification but clinically show similar symptoms such as joint pain and skin problems. As a result, the diagnosis is challenging, and usually, only broad treatments can be available. Consequently, the clinical responses in patients with different types of AIDs are unsatisfactory. Therefore, it is necessary to conduct more research to figure out the pathogenesis and therapeutic targets of AIDs. This requires research technologies with strong extraction and prediction capabilities. Single-cell sequencing technology analyses the genomic, epigenomic, or transcriptomic information at the single-cell level. It can define different cell types and states in greater detail, further revealing the molecular mechanisms that drive disease progression. These advantages enable cell biology research to achieve an unprecedented resolution and scale, bringing a whole new vision to life science research. In recent years, single-cell technology especially single-cell RNA sequencing (scRNA-seq) has been widely used in various disease research. In this paper, we present the innovations and applications of single-cell sequencing in the medical field and focus on the application contributing to the differential diagnosis and precise treatment of AIDs. Despite some limitations, single-cell sequencing has a wide range of applications in AIDs. We finally present a prospect for the development of single-cell sequencing. These ideas may provide some inspiration for subsequent research.

The future of single-use plastics in life science: Sterile printing of PLA reduces greenhouse gas emissions by 80% and enables carbon neutrality

The European Union’s Green Deal emphasizes life science and biotechnology as key drivers for achieving a circular economy. However, the prevalent use of non-sustainable single-use plastics derived from petrochemical sources in life science research and development contradicts this ecological goal. This study presents a viable alternative through on-site sterile 3D printing of single-use plastics using poly(lactic acid) (PLA). The sterile printing of PLA demonstrates a substantial reduction in CO2eq emissions per shake flask, decreasing from 260 g CO2eq to 145 g CO2eq. Suitability for cell culture was demonstrated for sterile printed PLA, autoclaved high-temperature PLA and for suspension cell cultures in shake flasks using CHO and insect cells as well as adherent Vero cell cultures in cell culture wells. Further optimization of sustainable shake flasks is achieved by utilizing recycled PLA, resulting in a remarkable reduction to 73 g CO2eq, constituting a 72% decrease in CO2eq emissions compared to conventional single-use plastics. Moreover, by employing geometric optimization to minimize material usage, emissions can be further reduced to 44 g CO2eq, representing an 83% reduction in CO2eq emissions. Anticipated advancements in PLA production suggest future carbon net negative PLA production, potentially achieving zero carbon emissions for single-use plastics using PLA. The exceptionally cost-effective nature of 3D printed single-use plastics, coupled with negligible capital costs for implementation, positions sterile 3D printing as a practical solution aligned with the 2030 Green Deal goals. Moreover, ongoing improvements in bioplastic production underscore the feasibility of meeting the 2050 targets of carbon neutrality for single-use plastics in life science research and development.

Capillary mediated vitrification is a novel technique that enables storage of antibody critical reagents at ambient temperature: Impact on binding, structure, and laboratory sustainability

Antibodies and antibody conjugates are essential components of life science research, but their inherent instability necessitates cold storage or lyophilization, posing logistical and sustainability challenges. Capillary-mediated vitrification has shown promise as a tool for improving biomolecule stability. In this study, we assess the feasibility of shipping and storing CMV-stabilized antibody reagents at ambient temperature using a purified rabbit polyclonal as a model system. The conditions tested included a simulated temperature excursion, ambient shipping, and storage for approximately two months at room-temperature. Antibody function was measured by both ELISA and Octet bio-layer interferometry kinetic measurements. Yield, aggregation, and thermal stability were assessed by UV/VIS, Size Exclusion Chromatography (SEC), thermal melting, and thermal aggregation studies. Results indicate >97 % protein yield and no impact on the binding activity. No evidence of aggregation or oligomer formation was detected. Addition of the vitrification buffer to the sample matrix resulted in an increase in the aggregation on-set temperature, indicating enhanced thermostability. A slight shift in both the SEC retention time for the main peak and a difference in aggregation behavior at high temperatures were noted post-vitrification. We hypothesize that these differences are related to the interaction of the protein with the saccharide component of the vitrification matrix and the stabilization mechanism of sugars. The cumulative data supports the use of Capillary Mediated Vitrification as a viable alternative to frozen reagent storage, with the potential to significantly impact reagent stability, assay performance, laboratory operations, and sustainability initiatives.

A simulated microgravity-oriented AIE probe-ECM hydrogel-integrated chip for cell culture and superoxide anion radical detection

Human space activities have been continuously increasing. Astronauts experiencing spaceflight are faced with health problems caused by special space environments such as microgravity, and the investigation of cell injury is fundamental. The development of a platform capable of cell culture and injury detection is the prerequisite for the investigation. Constructing a platform suitable for special conditions in space life science research is the key issue. The ground-based investigation is an indispensable part of the research. Accordingly, a simulated microgravity (SMG)-oriented integrated chip platform capable of 3D cell culture and in situ visual detection of superoxide anion radical (O2•−) is developed. SMG can cause oxidative stress in human cells, and O2•− is one of the signaling molecules. Thus, a O2•−-responsive aggregation-induced emission (AIE) probe is designed, which shows high selectivity and sensitivity to O2•−. Moreover, the probe exhibits abilities of long-term and wash-free staining to cells due to the AIE behavior, which is precious for space cell imaging. Meanwhile, a chip with a high-aspect-ratio chamber for adequate medium storage for the lack of the perfusion system during the SMG experiment and a cell culture chamber which can integrate the extracellular matrix (ECM) hydrogel for the bioinspired 3D cell culture is fabricated. In addition, a porous membrane is introduced between the chambers to prevent the hydrogel from separating during the SMG experiment. The afforded AIE probe-ECM hydrogel-integrated chip can achieve 3D culturing of U87-MG cells and in situ fluorescent detection of endogenous O2•− in the cells after long-term staining under SMG. The chip provides a powerful and potential platform for ground-based investigation in space life science and biomedical research.

Toothbrushing programme in Saudi Arabia ‘TOPS’: a study protocol for a cluster randomised controlled trial in kindergartens, Riyadh

IntroductionDental caries among children is a major global health problem and is a particular public health challenge in Saudi Arabia. Dental caries cause pain, infection and negatively impact quality of...