The role of the Arabidopsis E2FB transcription factor in regulating auxin-dependent cell division

The molecular mechanisms by which the phytohormone auxin coordinates cell division with cell growth and differentiation are largely unknown. Here, we show that in Arabidopsis thaliana E2FB, accumulation and stability are positively regulated by auxin. Coexpression of E2FB, but not of E2FA, with its dimerization partner A, stimulated cell proliferation in the absence of auxin in tobacco (Nicotiana tabacum) Bright Yellow-2 cells. E2FB regulated the entry into both S- and M-phases, the latter corresponding to the activation of a plant-specific mitotic regulator, CDKB1;1. Increased E2FB levels led to shortened cell cycle duration, elevated cell numbers, and extremely small cell sizes. In the absence of auxin, cells elongated with concomitant increase in their ploidy level, but both were strongly inhibited by E2FB. We conclude that E2FB is one of the key targets for auxin to determine whether cells proliferate or whether they exit the cell cycle, enlarge, and endoreduplicate their DNA.     

Design and synthesis of a series of bioavailable fatty acid synthase (FASN) KR domain inhibitors for cancer therapy

We designed and synthesized a new series of fatty acid synthase (FASN) inhibitors with potential utility for the treatment of cancer. Extensive SAR studies led to highly active FASN inhibitors with good cellular activity and oral bioavailability, exemplified by compound 34. Compound 34 is a potent inhibitor of human FASN (IC₅₀?=?28?nM) that effectively inhibits proliferation of A2780 ovarian cells (IC₅₀?=?13?nM) in lipid-reduced serum (LRS). This cellular activity can be rescued by addition of palmitate, consistent with an on-target effect. Compound 34 is also active in many other cell types, including PC3M (IC₅₀?=?25?nM) and LnCaP-Vancouver prostate cells (IC₅₀?=?66?nM), and is highly bioavailable (F 61%) with good exposure after oral administration. In a pharmacodynamics study in H460 lung xenograft-bearing mice, oral treatment with compound 34 results in elevated tumor levels of malonyl-CoA and decreased tumor levels of palmitate, fully consistent with the desired target engagement.     

Novel plant-specific cyclin-dependent kinase inhibitors induced by biotic and abiotic stresses

The EL2 gene of rice (Oryza sativa), previously classified as early response gene against the potent biotic elicitor N-acetylchitoheptaose and encoding a short polypeptide with unknown function, was identified as a novel cell cycle regulatory gene related to the recently reported SIAMESE (SIM) gene of Arabidopsis thaliana. Iterative two-hybrid screens, in vitro pull-down assays, and fluorescence resonance energy transfer analyses showed that Orysa; EL2 binds the cyclin-dependent kinase (CDK) CDKA1;1 and D-type cyclins. No interaction was observed with the plant-specific B-type CDKs. The amino acid motif ELERFL was identified to be essential for cyclin, but not for CDK binding. Orysa;EL2 impaired the ability of Orysa; CYCD5;3 to complement a budding yeast (Saccharomyces cerevisiae) triple CLN mutant, whereas recombinant protein inhibited CDK activity in vitro. Moreover, Orysa;EL2 was able to rescue the multicellular trichome phenotype of sim mutants of Arabidopsis, unequivocally demonstrating that Orysa;EL2 operates as a cell cycle inhibitor. Orysa;EL2 mRNA levels were induced by cold, drought, and propionic acid. Our data suggest that Orysa;EL2 encodes a new type of plant CDK inhibitor that links cell cycle progression with biotic and abiotic stress responses.     

The ins and outs of the plant cell cycle

Plant growth and development are driven by the continuous generation of new cells. Whereas much has been learned at a molecular level about the mechanisms that orchestrate progression through the different cell-cycle phases, little is known about how the cell-cycle machinery operates in the context of an entire plant and contributes to growth, cell differentiation and the formation of new tissues and organs. Here, we discuss how intrinsic developmental signals and environmental cues affect cell-cycle entry and exit.     

Real-time PCR assay for the simultaneous quantification of nitrifying and denitrifying bacteria in activated sludge

In order to improve wastewater treatment processes, a need exists for tools that rapidly give detailed insight into the community structure of activated sludge, supplementary to chemical and physical data. In this study, the advantages of microarrays and quantitative polymerase chin reaction (PCR) methods were combined into a real-time PCR assay that allows the simultaneous quantification of phylogenetic and functional genes involved in nitrification and denitrification processes. Simultaneous quantification was possible along a 5-log dynamic range and with high linear correlation (R ² > 0.98). The specificity of the assay was confirmed by cloning and sequencing analyses of PCR amplicons obtained from activated sludge. The real-time assay was validated on mixed liquid samples of different treatment plants, which varied in nitrogen removal rate. The abundance of ammonia oxidizers was in the order of magnitude of 10⁶ down to 10⁴ ml⁻¹, whereas nitrite oxidizers were less abundant (10³–10¹ order of magnitude). The results were in correspondence with the nitrite oxidation rate in the sludge types. As for the nirS, nirK, and nosZ gene copy numbers, their abundance was generally in the order of magnitude of 10⁸–10⁵. When sludge samples were subjected to lab-scale perturbations, a decrease in nitrification rate was reflected within 18 h in the copy numbers of nitrifier genes (decrease with 1 to 5 log units), whereas denitrification genes remained rather unaffected. These results demonstrate that the method is a fast and accurate tool for the analysis of the (de)nitrifying community structure and size in both natural and engineered environmental samples. Electronic supplementary material Supplementary material is available in the online version of this article at and is accessible for authorized users.     

Cultivation of denitrifying bacteria: optimization of isolation conditions and diversity study

An evolutionary algorithm was applied to study the complex interactions between medium parameters and their effects on the isolation of denitrifying bacteria, both in number and in diversity. Growth media with a pH of 7 and a nitrogen concentration of 3 mM, supplemented with 1 ml of vitamin solution but not with sodium chloride or riboflavin, were the most successful for the isolation of denitrifiers from activated sludge. The use of ethanol or succinate as a carbon source and a molar C/N ratio of 2.5, 20, or 25 were also favorable. After testing of 60 different medium parameter combinations and comparison with each other as well as with the standard medium Trypticase soy agar supplemented with nitrate, three growth media were highly suitable for the cultivation of denitrifying bacteria. All evaluated isolation conditions were used to study the cultivable denitrifier diversity of activated sludge from a municipal wastewater treatment plant. One hundred ninety-nine denitrifiers were isolated, the majority of which belonged to the Betaproteobacteria (50.4%) and the Alphaproteobacteria (36.8%). Representatives of Gammaproteobacteria (5.6%), Epsilonproteobacteria (2%), and Firmicutes (4%) and one isolate of the Bacteroidetes were also found. This study revealed a much more diverse denitrifying community than that previously described in cultivation-dependent research on activated sludge.     

Affordable artificial intelligence-based digital pathology for neglected tropical diseases: A proof-of-concept for the detection of soil-transmitted helminths and Schistosoma mansoni eggs in Kato-Katz stool thick smears

BackgroundWith the World Health Organization’s (WHO) publication of the 2021–2030 neglected tropical diseases (NTDs) roadmap, the current gap in global diagnostics became painfully apparent. Improving existing diagnostic standards with state-of-the-art technology and artificial intelligence has the potential to close this gap.Methodology/Principal findingsWe prototyped an artificial intelligence-based digital pathology (AI-DP) device to explore automated scanning and detection of helminth eggs in stool prepared with the Kato-Katz (KK) technique, the current diagnostic standard for diagnosing soil-transmitted helminths (STHs; Ascaris lumbricoides, Trichuris trichiura and hookworms) and Schistosoma mansoni (SCH) infections. First, we embedded a prototype whole slide imaging scanner into field studies in Cambodia, Ethiopia, Kenya and Tanzania. With the scanner, over 300 KK stool thick smears were scanned, resulting in total of 7,780 field-of-view (FOV) images containing 16,990 annotated helminth eggs (Ascaris: 8,600; Trichuris: 4,083; hookworms: 3,623; SCH: 684). Around 90% of the annotated eggs were used to train a deep learning-based object detection model. From an unseen test set of 752 FOV images containing 1,671 manually verified STH and SCH eggs (the remaining 10% of annotated eggs), our trained object detection model extracted and classified helminth eggs from co-infected FOV images in KK stool thick smears, achieving a weighted average precision (± standard deviation) of 94.9% ± 0.8% and a weighted average recall of 96.1% ± 2.1% across all four helminth egg species.Conclusions/SignificanceWe present a proof-of-concept for an AI-DP device for automated scanning and detection of helminth eggs in KK stool thick smears. We identified obstacles that need to be addressed before the diagnostic performance can be evaluated against the target product profiles for both STH and SCH. Given that these obstacles are primarily associated with the required hardware and scanning methodology, opposed to the feasibility of AI-based results, we are hopeful that this research can support the 2030 NTDs road map and eventually other poverty-related diseases for which microscopy is the diagnostic standard.