High-throughput Culture Research Articles

Bioremediation of Recalcitrant Xenobiotic Compounds: Advancements and Challenges

Widespread recalcitrant xenobiotic compounds have posed serious environmental threats. These compounds are known to contaminate groundwater, crops, water bodies, and lands, affecting the lives of people living nearby. Sites polluted with organic contaminants like polycyclic aromatic hydrocarbons (PAHs), chlorinated hydrocarbons (CHC), phenols, and aromatic hydrocarbons (benzene-toluene-ethylbenzene-xylenes, BTEX) are located worldwide, in both developed and developing countries. Many pollutants have been classified as persistent organic pollutants (POPs) whose production and usage have been either limited or banned by the Stockholm Convention. In May 2001, the Stockholm Convention gave a list of 12 POPs and called them “dirty dozens,” which has now increased to 36 POPs. Much advancement has been made in the last decade; however, on-field bioremediation techniques are still not well developed. Detection of ongoing remediation in trials by using metagenomics, metatranscriptomics, metabolomics, and metaproteomics produces huge data sets. These in-silico analyses required efficient algorithms and skilled professionals to contemplate data analyses. Carbon-stable isotope analysis, microarrays, and high-throughput cultivation techniques are also promising methods that have helped researchers track bioremediation. However, challenges faced by the scientific community are numerous, which has affected the pace of advancements in achieving a defined strategy for bioremediation of xenobiotic compounds. This review summarises the need for remediation of recalcitrant xenobiotic compounds that pose a threat to the environment and human health. Also, advancements made in the field of bioremediation and the problems posed in the implementation of designed strategies have been summed up.

Antibacterial, Resistance Modulation, Anti-Biofilm Formation, and Efflux Pump Inhibition Properties of Loeseneriella africana (Willd.) N. Halle (Celastraceae) Stem Extract and Its Constituents.

This study investigated the antibacterial, resistance modulation, biofilm inhibition, and efflux pump inhibition potentials of Loeseneriella africana stem extract and its constituents. The antimicrobial activity was investigated by the high-throughput spot culture growth inhibition (HT-SPOTi) and broth microdilution assays. The resistance modulation activity was investigated using the anti-biofilm formation and efflux pump inhibition assays. Purification of the extract was carried out by chromatographic methods, and the isolated compounds were characterized based on nuclear magnetic resonance, Fourier transform infrared and mass spectrometry spectral data and comparison with published literature. The whole extract, methanol, ethyl acetate, and pet-ether fractions of L. africana all showed antibacterial activity against the test bacteria with MICs ranging from 62.5 to 500.0 µg/mL The whole extract demonstrated resistance modulation effect through strong biofilm inhibition and efflux pump inhibition activities against S. aureus ATCC 25923, E. coli ATCC 25922 and P. aeruginosa ATCC 27853. Chromatographic fractionation of the ethyl acetate fraction resulted in the isolation of a triterpenoid (4S,4αS,6αR,6βS,8αS,12αS,12βR,14αS,14βR)-4,4α,6β,8α,11,11,12β,14α-Octamethyloctadecahydropicene-1,3(2H,4H)-dione) and a phytosterol (β-sitosterol). These compounds showed antibacterial activity against susceptible bacteria at a MIC range of 31-125 µg/mL and potentiated the antibacterial activity of amoxicillin (at ¼ MIC of compounds) against E. coli and P. aeruginosa with modulation factors of 32 and 10, respectively. These compounds also demonstrated good anti-biofilm formation effect at a concentration range of 3-100 µg/mL, and bacterial efflux pump inhibition activity at ½ MIC and ¼ MIC against E. coli and P. aeruginosa. Loeseneriella africana stem bark extracts and constituents elicit considerable antibacterial, resistance modulation, and biofilm and efflux pump inhibition activities. The results justify the indigenous uses of L. africana for managing microbial infections.

Advances in high throughput cell culture technologies for therapeutic screening and biological discovery applications.

Cellular phenotypes and functional responses are modulated by the signals present in their microenvironment, including extracellular matrix (ECM) proteins, tissue mechanical properties, soluble signals and nutrients, and cell-cell interactions. To better recapitulate and analyze these complex signals within the framework of more physiologically relevant culture models, high throughput culture platforms can be transformative. High throughput methodologies enable scientists to extract increasingly robust and broad datasets from individual experiments, screen large numbers of conditions for potential hits, better qualify and predict responses for preclinical applications, and reduce reliance on animal studies. High throughput cell culture systems require uniformity, assay miniaturization, specific target identification, and process simplification. In this review, we detail the various techniques that researchers have used to face these challenges and explore cellular responses in a high throughput manner. We highlight several common approaches including two-dimensional multiwell microplates, microarrays, and microfluidic cell culture systems as well as unencapsulated and encapsulated three-dimensional high throughput cell culture systems, featuring multiwell microplates, micromolds, microwells, microarrays, granular hydrogels, and cell-encapsulated microgels. We also discuss current applications of these high throughput technologies, namely stem cell sourcing, drug discovery and predictive toxicology, and personalized medicine, along with emerging opportunities and future impact areas.

Establishment of microbial model communities capable of removing trace organic chemicals for biotransformation mechanisms research

BackgroundRemoval of trace organic chemicals (TOrCs) in aquatic environments has been intensively studied. Some members of natural microbial communities play a vital role in transforming chemical contaminants, however, complex microbial interactions impede us from gaining adequate understanding of TOrC biotransformation mechanisms. To simplify, in this study, we propose a strategy of establishing reduced-richness model communities capable of removing diverse TOrCs via pre-adaptation and dilution-to-extinction.ResultsMicrobial communities were adapted from tap water, soil, sand, sediment deep and sediment surface to changing concentrations of 27 TOrCs mixture. After adaptation, the communities were further diluted to reduce diversity into 96 deep well plates for high-throughput cultivation. After characterizing microbial structure and TOrC removal performance, thirty taxonomically non-redundant model communities with different removal abilities were obtained. The pre-adaptation process was found to reduce the microbial richness but to increase the evenness and phylogenetic diversity of resulting model communities. Moreover, phylogenetic diversity showed a positive effect on the number of TOrCs that can be transformed simultaneously. Pre-adaptation also improved the overall TOrC removal rates, which was found to be positively correlated with the growth rates of model communities.ConclusionsThis is the first study that investigated a wide range of TOrC biotransformation based on different model communities derived from varying natural microbial systems. This study provides a standardized workflow of establishing model communities for different metabolic purposes with changeable inoculum and substrates. The obtained model communities can be further used to find the driving agents of TOrC biotransformation at the enzyme/gene level.

A computer vision and residual neural network (ResNet) combined method for automated and accurate yeast replicative aging analysis of high-throughput microfluidic single-cell images

With the rapid development of microfluidic platforms in high-throughput single-cell culturing, laborious operation to manipulate massive budding yeast cells (Saccharomyces cerevisiae) in replicative aging studies has been greatly simplified and automated. As a result, large datasets of microscopy images bring challenges to fast and accurately determine yeast replicative lifespan (RLS), which is the most important parameter to study cell aging. Based on our microfluidic diploid yeast long-term culturing (DYLC) chip that features 1100 traps to immobilize single cells and record their proliferation and aging via time-lapse imaging, herein, a dedicated algorithm combined with computer vision and residual neural network (ResNet) was presented to efficiently process tremendous micrographs in a high-throughput and automated manner. The image-processing algorithm includes following pivotal steps: (i) segmenting multi-trap micrographs into time-lapse single-trap sub-images, (ii) labeling 8 yeast budding features and training the 18-layer ResNet, (iii) converting the ResNet predictions in analog values into digital signals, (iv) recognizing cell dynamic events, and (v) determining yeast RLS and budding time interval (BTI) ultimately. The ResNet algorithm achieved high F1 scores (over 92%) demonstrating the effectiveness and accuracy in the recognition of yeast budding events, such as bud appearance, daughter dissection and cell death. Therefore, the results conduct that similar deep learning algorithms could be tailored to analyze high-throughput microscopy images and extract multiple cell behaviors in microfluidic single-cell analysis.

Automated high-throughput cell culture scratch assay identifies wound healing promoting and inhibiting compounds from a small compound library of redox active molecules

Automated high-throughput cell culture scratch assay identifies wound healing promoting and inhibiting compounds from a small compound library of redox active molecules

Comparative analysis between zebrafish and an automated live-cell assay to classify developmental neurotoxicant chemicals

Modern toxicology's throughput has dramatically increased due to alternative models, laboratory automation, and machine learning. This has enabled comparative studies across species and assays to prioritize chemical hazard potential and to understand how different model systems might complement one another. However, such comparative studies of high-throughput data are still in their infancy, with more groundwork needed to firmly establish the approach. Therefore, this study aimed to compare the bioactivity of the NIEHS Division of Translational Toxicology's (DTT) 87-compound developmental neurotoxicant (DNT) library in zebrafish and an in vitro high-throughput cell culture system. The early life-stage zebrafish provided a whole animal approach to developmental toxicity assessment. Chemical hits for abnormalities in embryonic zebrafish morphology, mortality, and behavior (ZBEscreen™) were compared with chemicals classified as high-risk by the Cell Health Index (CHI™), which is an outcome class probability from a machine learning classifier using 12 parameters from the SYSTEMETRIC® Cell Health Screen (CHS). The CHS was developed to assess human toxicity risk using supervised machine learning to classify acute cell stress phenotypes in a human leukemia cell line (HL60 cells) following a 4-h exposure to a chemical of interest. Due to the design of the screen, the zebrafish assays were more exhaustive, yielding 86 total bioactive hits, whereas the SYSTEMETRIC® CHS focusing on acute toxicity identified 20 chemicals as potentially toxic. The zebrafish embryonic and larval photomotor response assays (EPR and LPR, respectively) detected 40 of the 47 chemicals not found by the zebrafish morphological screen and CHS. Collectively, these results illustrate the advantages of using two alternative models in tandem for rapid hazard assessment and chemical prioritization and the effectiveness of CHI™ in identifying toxicity within a single multiparametric assay.

Biological functions of endophytic bacteria in Robinia pseudoacacia 'Hongsen'.

Endophytes and their host plants have co-evolved for a very long time. This relationship has led to the general recognition of endophytes as a particular class of microbial resources. R. pseudoacacia 'Hongsen' is drought- and barren-resistant species that can be grown in both the north and south of China, efficiently addresses the ecological issues caused by China's 'southern eucalyptus and northern poplar. Up to date, cultured-dependent studies are available for the R. pseudoacacia nitrogen-fixing and other endophytes. Therefore, the present research studied the R. pseudoacacia 'Hongsen,' microbiome in detail by high-throughput sequencing and culture dependant. This study examined microbial species and functional diversity in Robinia pseudoacacia 'Hongsen' using culture-dependent (isolation) and culture-independent techniques. A total of 210 isolates were isolated from R. pseudoacacia 'Hongsen.' These isolates were clustered into 16 groups by the In Situ PCR (IS-PCR) fingerprinting patterns. 16S rRNA gene sequence analysis of the representative strain of each group revealed that these groups belonged to 16 species of 8 genera, demonstrating the diversity of endophytes in R. pseudoacacia 'Hongsen'. 'Bacillus is the most prevalent genus among all the endophytic bacteria. High-throughput sequencing of endophytic bacteria from R. pseudoacacia 'Hongsen' of the plant and the rhizosphere soil bacteria showed that the bacterial populations of soil near the root, leaf, and rhizosphere differed significantly. The microbial abundance decreased in the endophytes as compared to the rhizosphere. We observed a similar community structure of roots and leaves. With and without root nodules, Mesorhizobium sp. was significantly different in R. pseudoacacia 'Hongsen' plant. It was predicted that R. pseudoacacia 'Hongsen' plant endophytic bacteria would play a significant role in the metabolic process, such as carbohydrate metabolism, amino acid metabolism, membrane transport, and energy metabolism.

Development of a novel microplate for high-throughput screening and optimization of DHA producing strains based on CFD technology.

Microtiter plates are suitable for screening and process development of most microorganisms. They are currently the container of choice for high-throughput and small-scale microbial culture, but require optimization for specific work. In this research, a novel type of microtiter plate was developed using computational fluid dynamics (CFD) technology. The new plate provided high oxygen supply and optimal mixing effects for the fermentation culture of docosahexaenoic acid (DHA) producing strains, surpassing the conventional method of strain screening with shake flasks, which was insufficient. The shape of the microtiter plate was modified, and baffles were introduced to improve mass transfer and oxygen supply effects in the vibrating bioreactor. CFD technology was used to model the new plate's characteristics, establishing the superiority of hexagonal microtiter plates with six baffles. Parameters in the incubation process, such as vibration frequency and liquid load, were optimized, and the final result achieved an oxygen transfer coefficient (KL a) of 0.61s-1 and a volume power input of 2364 wm-3 , which was four to five times better than the original 96-well plate. The culture results optimized by the model were also verified. Therefore, this new microtiter plate provides a powerful tool for future high-throughput screening of strains.

Urban biogeography of fungal endophytes across San Francisco.

In natural and agricultural systems, the plant microbiome-the microbial organisms associated with plant tissues and rhizosphere soils-has been shown to have important effects on host physiology and ecology, yet we know little about how these plant-microbe relationships play out in urban environments. Here we characterize the composition of fungal communities associated with living leaves of one of the most common sidewalk trees in the city of San Francisco, California. We focus our efforts on endophytic fungi (asymptomatic microfungi that live inside healthy leaves), which have been shown in other systems to have large ecological effects on the health of their plant hosts. Specifically, we characterized the foliar fungal microbiome of Metrosideros excelsa (Myrtaceae) trees growing in a variety of urban environmental conditions. We used high-throughput culturing, PCR, and Sanger sequencing of the internal transcribed spacer nuclear ribosomal DNA (ITS nrDNA) region to quantify the composition and structure of fungal communities growing within healthy leaves of 30 M. excelsa trees from six distinct sites, which were selected to capture the range of environmental conditions found within city limits. Sequencing resulted in 854 high-quality ITS sequences. These sequences clustered into 85 Operational Taxonomic Units (97% OTUs). We found that these communities encompass relatively high alpha (within) and beta (between-site) diversity. Because the communities are all from the same host tree species, and located in relatively close geographical proximity to one another, these analyses suggest that urban environmental factors such as heat islands or differences in vegetation or traffic density (and associated air quality) may potentially be influencing the composition of these fungal communities. These biogeographic patterns provide evidence that plant microbiomes in urban environments can be as dynamic and complex as their natural counterparts. As human populations continue to transition out of rural areas and into cities, understanding the factors that shape environmental microbial communities in urban ecosystems stands to become increasingly important.

Nonlinear state estimation as tool for online monitoring and adaptive feed in high throughput cultivations.

Robotic facilities that can perform advanced cultivations (e.g., fed-batch or continuous) in high throughput have drastically increased the speed and reliability of the bioprocess development pipeline. Still, developing reliable analytical technologies,that can cope with the throughput of the cultivation system, has proven to be very challenging. On the one hand, the analytical accuracy suffers from the low sampling volumes, and on the other hand, the number of samples that must be treated rapidly is very large. These issues have been a major limitation for the implementation of feedback control methods in miniaturized bioreactor systems, where observations of the process states are typically obtained after the experiment has finished. In this work, we implement a Sigma-Point Kalman Filter in a high throughput platform with 24 parallel experiments at the mL-scale to demonstrate its viability and added value in high throughput experiments. The filter exploits the information generated by the ammonia-based pH control to enable the continuous estimation of the biomass concentration, a critical state to monitor the specific rates of production and consumption in the process. The objective in the selected case study is to ensure that the selected specific substrate consumption rate is tightly controlled throughout the complete Escherichia coli cultivations for recombinant production of an antibody fragment.

Microenvironmental reprogramming of human dermal papilla cells for hair follicle tissue engineering.

The restoration of hair-inductive potential in human dermal papilla cells (hDPCs) is a tremendous challenge for hair regeneration. Much of the research thus far has indicated that three-dimensional (3-D) culture shows improved efficacy in hair follicle (HF) neogenesis. However, mature HF cannot regenerate in an incomplete microenvironment. This study developed an optimized 3-D co-culture system to restore the hair-inductive characteristics of hDPCs by mimicking the in-vivo microenvironment. As a result, Matrigel-encapsulated hDPCs spontaneously formed into hDPC aggregates (hDPAs), which exhibited better activity, higher proliferation rates, and less apoptosis and hypoxia than the ultra-low attachment culture. Interestingly, the co-culture with the hair matrix cells and dermal sheath cup cells further enhanced the expression of hair regeneration-related genes of hDPAs compared to conditioned medium and improved mature HF induction. In addition, these hDPAs with higher hair inductivity could be produced on a large scale and easily separated for gene expression detection. Finally, the mRNA sequencing, PCR, and WB results showed that the co-culture biomimetic microenvironment stimulated the canonical Wnt signaling pathway and inhibited the BMP signaling pathway. Thus, this co-culture system will provide a reliable platform that allows high-throughput culture, testing, and harvesting of hDPAs for HF tissue engineering. STATEMENT OF SIGNIFICANCE: Extensive hair loss continues to be difficult to treat and causes significant patient morbidity. Hair follicle (HF) tissue engineering may seem to be a way out. However, the absence of the in-vivo microenvironment fails to regenerate mature hairs. This study systematically described a biomimetic co-culture approach to generate better quality human dermal papilla cell aggregates (hDPAs) with improved hair inductive properties, which can be further used for HF tissue engineering. The hDPC microenvironment was reprogrammed through the controllable formation of self-assembled organoids in Matrigel and the tri-culture with hair matrix cells and dermal sheath cup cells. This work indicates that the production of hDPAs could be readily scaled, in theory for large-scale assays, analyses, or therapeutic applications.

A highly versatile biopolymer-based platform for the maturation of human pluripotent stem cell-derived cardiomyocytes enables functional analysis in vitro and 3D printing of heart patches.

Human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) represent a valuable tool for in vitro modeling of the cardiac niche and possess great potential in tissue engineering applications. However, conventional polystyrene-based cell culture substrates have adverse effects on cardiomyocytes in vitro due to the stress applied by a stiff substrate on contractile cells. Ultra-high viscosity alginates offer a unique versatility as tunable substrates for cardiac cell cultures due to their biocompatibility, flexible biofunctionalization, and stability. In this work, we analyzed the effect of alginate substrates on hPSC-CM maturity and functionality. Alginate substrates in high-throughput compatible culture formats fostered a more mature gene expression and enabled the simultaneous assessment of chronotropic and inotropic effects upon beta-adrenergic stimulation. Furthermore, we produced 3D-printed alginate scaffolds with differing mechanical properties and plated hPSC-CMs on the surface of these to create Heart Patches for tissue engineering applications. These exhibited synchronous macro-contractions in concert with more mature gene expression patterns and extensive intracellular alignment of sarcomeric structures. In conclusion, the combination of biofunctionalized alginates and human cardiomyocytes represents a valuable tool for both in vitro modeling and regenerative medicine, due to its beneficial effects on cardiomyocyte physiology, the possibility to analyze cardiac contractility, and its applicability as Heart Patches.

High-throughput longitudinal electrophysiology screening of mature chamber-specific hiPSC-CMs using optical mapping

hiPSC-CMs are being considered by the Food and Drug Administration and other regulatory agencies for invitro cardiotoxicity screening to provide human-relevant safety data. Widespread adoption of hiPSC-CMs in regulatory and academic science is limited by the immature, fetal-like phenotype of the cells. Here, to advance the maturation state of hiPSC-CMs, we developed and validated a human perinatal stem cell-derived extracellular matrix coating applied to high-throughput cell culture plates. We also present and validate a cardiac optical mapping device designed for high-throughput functional assessment of mature hiPSC-CM action potentials using voltage-sensitive dye and calcium transients using calcium-sensitive dyes or genetically encoded calcium indicators (GECI, GCaMP6). We utilize the optical mapping device to provide new biological insight into mature chamber-specific hiPSC-CMs, responsiveness to cardioactive drugs, the effect of GCaMP6 genetic variants on electrophysiological function, and the effect of daily β-receptor stimulation on hiPSC-CM monolayer function and SERCA2a expression.

Alcanivorax quisquiliarum sp. nov., isolated from anaerobic fermentation liquid of food waste by high-throughput cultivation.

Strain CY1518T was isolated from an anaerobic fermentation liquid of food waste treatment plant in Beijing, PR China, and characterized to assess its taxonomy. Cells of CY1518T were Gram-stain-negative, oxidase-negative, catalase-positive and ellipsoidal. Growth occurred at 20-42 °C (optimum, 37 °C), pH 6.0-10.0 (optimum, pH 8) and with 0-6.0 % (w/v) NaCl (optimum, 1.5%). Phylogenetic analysis based on 16S rRNA gene sequences indicated that strain CY1518T belongs to the genus Alcanivorax, with the highest sequence similarity to Alcanivorax pacificus W11-5T (95.97 %), followed by Alcanivorax indicus SW127T (95.08%). The similarity between strain CY1518T and other strains of Alcanivorax was less than 95 %. The genomic DNA G+C content of strain CY1518T was 60.88 mol%. The average nucleotide identity, average amino acid identity and digital DNA-DNA hybridization values between strain CY1518T and the closely related taxa A. pacificus W11-5T and A. indicus SW127T were 77.61, 78.03 and 21.2 % and 74.15, 70.02 and 19.3%, respectively. The strain was able to use d-serine, Tween 40 and some organic acid compounds for growth. The polar lipids comprised aminophospholipid, diphosphatidylglycerol, glycolipid, an unknown polar lipid, phosphatidylethanolamine, phosphatidylglycerol and phospholipid. The principal fatty acids (>5 %) were C19 : 0 cyclo ω8c (36.3%), C16 : 0 (32.3%), C12 : 0 3-OH (8.3%) and C12 : 0 (7.6%). Based on its phenotypic, genotypic and genomic characteristics, strain CY1518T represents a novel species in the genus Alcanivorax, for which the name Alcanivorax quisquiliarum sp. nov. is proposed. The type strain is CY1518T (=GDMCC 1.2918T=JCM 35120T).

Large-scale high-throughput 3D culture, imaging, and analysis of cell spheroids using microchip-enhanced light-sheet microscopy.

Light sheet microscopy combined with a microchip is an emerging tool in biomedical research that notably improves efficiency. However, microchip-enhanced light-sheet microscopy is limited by noticeable aberrations induced by the complex refractive indices in the chip. Herein, we report a droplet microchip that is specifically engineered to be capable of large-scale culture of 3D spheroids (over 600 samples per chip) and has a polymer index matched to water (difference <1%). When combined with a lab-built open-top light-sheet microscope, this microchip-enhanced microscopy technique allows 3D time-lapse imaging of the cultivated spheroids with ∼2.5-µm single-cell resolution and a high throughput of ∼120 spheroids per minute. This technique was validated by a comparative study on the proliferation and apoptosis rates of hundreds of spheroids with or without treatment with the apoptosis-inducing drug Staurosporine.

Naming new taxa of prokaryotes in the 21st century.

The nomenclature of prokaryotes is regulated by the rules of the International Code of Nomenclature of Prokaryotes (ICNP) and is based on the Linnaean binomial system. The current rules of the Code only cover the nomenclature of the cultivated minority. Proposals to incorporate the uncultivated majority of bacteria and archaea under the rules of the Code were recently rejected by the International Committee on Systematics of Prokaryotes. The provisional rank of Candidatus can be used to name uncultivated prokaryotes whose names cannot be validly published under the rules of the ICNP, but their names can now be validated under the Code of Nomenclature of Prokaryotes Described from Sequence Data (the SeqCode), which was recently established to cover the nomenclature of the uncultivated majority. Metagenomics, single-cell genomics, and high-throughput cultivation techniques have led to a flood of new organisms currently waiting to be named. Automated programs such as GAN and Protologger can assist researchers in naming and describing newly discovered prokaryotes, cultivated as well as uncultivated. However, Latin and Greek skills remain indispensable for proper quality control of names that must meet the standards set by the codes of nomenclature.

SnakeMAGs: a simple, efficient, flexible and scalable workflow to reconstruct prokaryotic genomes from metagenomes.

Background: Over the last decade, we have observed in microbial ecology a transition from gene-centric to genome-centric analyses. Indeed, the advent of metagenomics combined with binning methods, single-cell genome sequencing as well as high-throughput cultivation methods have contributed to the continuing and exponential increase of available prokaryotic genomes, which in turn has favored the exploration of microbial metabolisms. In the case of metagenomics, data processing, from raw reads to genome reconstruction, involves various steps and software which can represent a major technical obstacle. Methods: To overcome this challenge, we developed SnakeMAGs, a simple workflow that can process Illumina data, from raw reads to metagenome-assembled genomes (MAGs) classification and relative abundance estimate. It integrates state-of-the-art bioinformatic tools to sequentially perform: quality control of the reads (illumina-utils, Trimmomatic), host sequence removal (optional step, using Bowtie2), assembly (MEGAHIT), binning (MetaBAT2), quality filtering of the bins (CheckM, GUNC), classification of the MAGs (GTDB-Tk) and estimate of their relative abundance (CoverM). Developed with the popular Snakemake workflow management system, it can be deployed on various architectures, from single to multicore and from workstation to computer clusters and grids. It is also flexible since users can easily change parameters and/or add new rules. Results: Using termite gut metagenomic datasets, we showed that SnakeMAGs is slower but allowed the recovery of more MAGs encompassing more diverse phyla compared to another similar workflow named ATLAS.Importantly, these additional MAGs showed no significant difference compared to the other ones in terms of completeness, contamination, genome size nor relative abundance. Conclusions: Overall, it should make the reconstruction of MAGs more accessible to microbiologists. SnakeMAGs as well as test files and an extended tutorial are available at https://github.com/Nachida08/SnakeMAGs.

A novel and cost-effective method for high-throughput 3D culturing and rhythmic assessment of hiPSC-derived cardiomyocytes using retroreflective Janus microparticles

BackgroundHuman induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) gain attention as a potent cell source in regenerative medicine and drug discovery. With the necessity of the demands for experimental models to create a more physiologically relevant model of the heart in vitro we herein investigate a 3D culturing platform and a method for assessing rhythm in hiPSC-CMs.MethodsThe 3D cell culture PAMCELL™ plate is designed to enable cells to attach exclusively to adhesive patterned areas. These cell adhesive zones, named as micro-patterned pads, feature micron silica beads that are surface-modified with the well-known arginyl-glycyl-aspartic acid (RGD) peptide. RGD binding to the surface of hiPSC-CMs facilitates cell–cell attachment and the formation of uniform-size spheroids, which is controlled by the diameter of the micro-patterned pads. The assessment and evaluation of 3D hiPSC-CMs beating pattern are carried out using reflective properties of retroreflective Janus micro-particle (RJP). These RJPs are modified with an antibody targeting the gap junction protein found on the surface of hiPSC-CM spheroids. The signal assessment system comprises a camera attached to an optical microscope and a white light source.ResultsThe 3D PAMCELL™ R100 culture plate efficiently generate approximately 350 uniform-sized hiPSC-CM spheroids in each well of a 96-well plate and supported a 20-day culture. Analysis of genes and protein expression levels reveal that iPSC-CM spheroids grown on PAMCELL™ R100 retain cardiac stem cell characteristics and functions, outperforming traditional 2D culture platform. Additionally, the RJPs enable monitoring and evaluation of in vitro beating properties of cardiomyocytes without using complex monitoring setup. The system demonstrates its capability to identify alteration in the rhythmic activity of cardiac cells when exposed to ion channel blockers, nifedipine and E4031.ConclusionsThe integration of the 3D culture method and RJPs in this study establishes a platform for evaluating the rhythmic properties of 3D hiPSC-CMs. This approach holds significant potential for identifying arrhythmias or other cardiac abnormalities, ultimately contributing to the development of more effective therapies for heart diseases.Graphical

Model predictive control and moving horizon estimation for adaptive optimal bolus feeding in high-throughput cultivation of E. coli

We discuss the application of a nonlinear model predictive control (MPC) and moving horizon estimation (MHE) framework to achieve optimal operation of E. coli fed-batch cultivations with intermittent bolus feeding. 24 parallel experiments were considered in a high-throughput mini-bioreactor platform at a 10 mL scale. The robotic facility can run up to 48 fed-batch processes in parallel with automated liquid handling, online and at-line analytics. Three main challenges emerge in implementing the model-based monitoring and control framework: First, the inputs are given in an instantaneous pulsed form by bolus injections; second, online and at-line measurement frequencies are severely imbalanced; and third, optimization for the distinctive multiple reactors can be either parallelized or integrated. We address these challenges by incorporating the concept of impulsive control systems, formulating multi-rate MHE with identifiability analysis, and suggesting criteria for deciding the reactor configuration. In this study, we present the key elements and background theory of the implementation with in silico simulations for bacterial fed-batch cultivations.