Fully automated compound screening in Arabidopsis thaliana seedlings

High-throughput small molecule screenings in model plants are of great value to identify compounds that interfere with plant developmental processes. In academic research, the plant Arabidopsis thaliana is the most commonly used model organism for this purpose. However, compared to plant cellular systems, A. thaliana plants are less amenable to develop high-throughput screening assays. In this chapter, we describe a screening procedure that is compatible with liquid handling systems and increases the throughput of compound screenings in A. thaliana seedlings

Evaluation of commonly used ectoderm markers in iPSC trilineage differentiation.

Patient-derived induced pluripotent stem cells (iPSCs) have become a promising resource for exploring genetics of complex diseases, discovering new drugs, and advancing regenerative medicine. Increasingly, laboratories are creating their own banks of iPSCs derived from diverse donors. However, there are not yet standardized guidelines for qualifying these cell lines, i.e., distinguishing between bona fide human iPSCs, somatic cells, and imperfectly reprogrammed cells. Here, we report the establishment of a panel of 30 iPSCs from CD34+ peripheral blood mononuclear cells, of which 10 were further differentiated in vitro into all three germ layers. We characterized these different cell types with commonly used pluripotent and lineage specific markers, and showed that NES, TUBB3, and OTX2 cannot be reliably used as ectoderm differentiation markers. Our work highlights the importance of marker selection in iPSC authentication, and the need for the field to establish definitive standard assays

Association of ACE and NOS3 Gene Polymorphisms with Blood Pressure in a Case Control Study of Coronary Artery Disease in Punjab, Pakistan

Single nucleotide polymorphisms (SNPs), ACE rs4341 and NOS3 rs1799983 have been reported to be associated with coronary artery disease (CAD) and blood pressure (BP)in many but not all studies. We aimed to investigate the effect of these SNPs on BP and CAD in people from Punjab, Pakistan. A total of 650 subjects (430 CAD cases and 220 controls) were genotyped by TaqMan/KASPar allelic discrimination technique. Two BP measurements were reordered and their mean was calculated. The results showed that the risk allele frequencies (RAFs) of both SNPs were higher in cases than controls but the difference was not statistically significant. For rs4341, RAF in cases and controls was 0.577 vs. 0.525, p = 0.08 and for rs1799983, the RAF was 0.202 vs. 0.178, p = 0.31. The SNPs were not associated with CAD. The CAD odds ratio of rs4341 (1.22,0.97-1.53, p = 0.09) and that of rs1799983 (1.15, 0.86-1.54, p=0.33) was not statistically significant. Mean systolic blood pressure (SBP) and diastolic blood pressure (DBP) were significantly higher in cases than controls (p<0.05) and the SNPs showed a significant association with BP. Each risk allele of rs4341 (G) increased SBP by 10.04±0.8 mmHg and DBP by 2.5±0.6mmHg, while risk allele of rs1799983 (T), increased SBP and DBP by 16.4±0.9mmHg and 8.8±0.6mmHg respectively, all were statistically significant (p<0.05). When a combined effect of genotypes of both SNPs was examined, a significant effect on CAD outcome (p=0.01) was observed when GG of rs4341 and GT of rs1799983 co-existed. Similarly, maximum elevation in BP was observed when risk alleles of both SNPs in homozygous form (GG and TT) appeared together. In conclusion, the SNPs were not independently associated with CAD but were associated with BP in Pakistani subjects under study and may be causing CAD by modulating BP

X-CHIP: an integrated platform for high-throughput protein crystallization and on-the-chip X-ray diffraction data collection

The X-CHIP (X-ray Crystallography High-throughput Integrated Platform) is a novel microchip that has been developed to combine multiple steps of the crystallographic pipeline from crystallization to diffraction data collection on a single device to streamline the entire process

Integrating proteomic, sociodemographic and clinical data to predict future depression diagnosis in subthreshold symptomatic individuals

Funder: Stanley Medical Research Institute (SMRI); doi: https://doi.org/10.13039/100007123Abstract: Individuals with subthreshold depression have an increased risk of developing major depressive disorder (MDD). The aim of this study was to develop a prediction model to predict the probability of MDD onset in subthreshold individuals, based on their proteomic, sociodemographic and clinical data. To this end, we analysed 198 features (146 peptides representing 77 serum proteins (measured using MRM-MS), 22 sociodemographic factors and 30 clinical features) in 86 first-episode MDD patients (training set patient group), 37 subthreshold individuals who developed MDD within two or four years (extrapolation test set patient group), and 86 subthreshold individuals who did not develop MDD within four years (shared reference group). To ensure the development of a robust and reproducible model, we applied feature extraction and model averaging across a set of 100 models obtained from repeated application of group LASSO regression with ten-fold cross-validation on the training set. This resulted in a 12-feature prediction model consisting of six serum proteins (AACT, APOE, APOH, FETUA, HBA and PHLD), three sociodemographic factors (body mass index, childhood trauma and education level) and three depressive symptoms (sadness, fatigue and leaden paralysis). Importantly, the model demonstrated a fair performance in predicting future MDD diagnosis of subthreshold individuals in the extrapolation test set (AUC = 0.75), which involved going beyond the scope of the model. These findings suggest that it may be possible to detect disease indications in subthreshold individuals up to four years prior to diagnosis, which has important clinical implications regarding the identification and treatment of high-risk individuals

Antagonism between Bacteriostatic and Bactericidal Antibiotics Is Prevalent

Combination therapy is rarely used to counter the evolution of resistance in bacterial infections. Expansion of the use of combination therapy requires knowledge of how drugs interact at inhibitory concentrations. More than 50 years ago, it was noted that, if bactericidal drugs are most potent with actively dividing cells, then the inhibition of growth induced by a bacteriostatic drug should result in an overall reduction of efficacy when the drug is used in combination with a bactericidal drug. Our goal here was to investigate this hypothesis systematically. We first constructed time-kill curves using five different antibiotics at clinically relevant concentrations, and we observed antagonism between bactericidal and bacteriostatic drugs. We extended our investigation by performing a screen of pairwise combinations of 21 different antibiotics at subinhibitory concentrations, and we found that strong antagonistic interactions were enriched significantly among combinations of bacteriostatic and bactericidal drugs. Finally, since our hypothesis relies on phenotypic effects produced by different drug classes, we recreated these experiments in a microfluidic device and performed time-lapse microscopy to directly observe and quantify the growth and division of individual cells with controlled antibiotic concentrations. While our single-cell observations supported the antagonism between bacteriostatic and bactericidal drugs, they revealed an unexpected variety of cellular responses to antagonistic drug combinations, suggesting that multiple mechanisms underlie the interactions

Cluster-Assembled Nanoporous Super-Hydrophilic Smart Surfaces for On-Target Capturing and Processing of Biological Samples for Multi-Dimensional MALDI-MS

Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) on cluster-assembled super-hydrophilic nanoporous titania films deposited on hydrophobic conductive-polymer substrates feature a unique combination of surface properties that significantly improve the possibilities of capturing and processing biological samples before and during the MALDI-MS analysis without changing the selected sample target (multi-dimensional MALDI-MS). In contrast to pure hydrophobic surfaces, such films promote a remarkable biologically active film porosity at the nanoscale due to the soft assembling of ultrafine atomic clusters. This unique combination of nanoscale porosity and super-hydrophilicity provides room for effective sample capturing, while the hydrophilic-hydrophobic discontinuity at the border of the dot-patterned film acts as a wettability-driven containment for sample/reagent droplets. In the present work, we evaluate the performance of such advanced surface engineered reactive containments for their benefit in protein sample processing and characterization. We shortly discuss the advantages resulting from the introduction of the described chips in the MALDI-MS workflow in the healthcare/clinical context and in MALDI-MS bioimaging (MALDI-MSI)

Cell Lineage Analysis of the Mammalian Female Germline

Fundamental aspects of embryonic and post-natal development, including maintenance of the mammalian female germline, are largely unknown. Here we employ a retrospective, phylogenetic-based method for reconstructing cell lineage trees utilizing somatic mutations accumulated in microsatellites, to study female germline dynamics in mice. Reconstructed cell lineage trees can be used to estimate lineage relationships between different cell types, as well as cell depth (number of cell divisions since the zygote). We show that, in the reconstructed mouse cell lineage trees, oocytes form clusters that are separate from hematopoietic and mesenchymal stem cells, both in young and old mice, indicating that these populations belong to distinct lineages. Furthermore, while cumulus cells sampled from different ovarian follicles are distinctly clustered on the reconstructed trees, oocytes from the left and right ovaries are not, suggesting a mixing of their progenitor pools. We also observed an increase in oocyte depth with mouse age, which can be explained either by depth-guided selection of oocytes for ovulation or by post-natal renewal. Overall, our study sheds light on substantial novel aspects of female germline preservation and development

Automated liquid-handling operations for robust, resilient, and efficient bio-based laboratory practices

Increase in the adoption of liquid handling devices (LHD) can facilitate experimental activities. Initially adopted by businesses and industry-based laboratories, the practice has also moved to academic environments, where a wide range of non-standard/non-typical experiments can be performed. Current protocols or laboratory analyses require researchers to transfer liquids for the purpose of dilution, mixing, or inoculation, among other operations. LHD can render laboratories more efficient by performing more experiments per unit of time, by making operations robust and resilient against external factors and unforeseen events such as the COVID-19 pandemic, and by remote operation. The present work reviews literature that reported the adoption and utilisation of LHD available in the market and presents examples of their practical use. Applications demonstrate the critical role of automation in research development and its ability to reduce human intervention in the experimental workflow. Ultimately, this work will provide guidance to academic researchers to determine which LHD can fulfil their needs and how to exploit their use in both conventional and non-conventional applications. Furthermore, the breadth of applications and the scarcity of academic institutions involved in research and development that utilise these devices highlights an important area of opportunity for shift in technology to maximize research outcomes

The role of Holliday junction resolvases in the repair of spontaneous and induced DNA damage

DNA double-strand breaks (DSBs) and other lesions occur frequently during cell growth and in meiosis. These are often repaired by homologous recombination (HR). HR may result in the formation of DNA structures called Holliday junctions (HJs), which need to be resolved to allow chromosome segregation. Whereas HJs are present in most HR events in meiosis, it has been proposed that in vegetative cells most HR events occur through intermediates lacking HJs. A recent screen in yeast has shown HJ resolution activity for a protein called Yen1, in addition to the previously known Mus81/Mms4 complex. Yeast strains deleted for both YEN1 and MMS4 show a reduction in growth rate, and are very sensitive to DNA-damaging agents. In addition, we investigate the genetic interaction of yen1 and mms4 with mutants defective in different repair pathways. We find that in the absence of Yen1 and Mms4 deletion of RAD1 or RAD52 have no further effect, whereas additional sensitivity is seen if RAD51 is deleted. Finally, we show that yeast cells are unable to carry out meiosis in the absence of both resolvases. Our results show that both Yen1 and Mms4/Mus81 play important (although not identical) roles during vegetative growth and in meiosis