TPCK inhibits AGC kinases by direct activation loop adduction at phenylalanine-directed cysteine residues

N-alpha-tosyl-l-phenylalanyl chloromethyl ketone (TPCK) has anti-tumorigenic properties, but its direct cellular targets are unknown. Previously, we showed TPCK inhibited the PDKl-dependent AGC kinases RSK, Akt and S6K1 without inhibiting PKA, ERK1/2, PI3K, and PDK1 itself. Here we show TPCK-inhibition of the RSK-related kinases MSK1 and 2, which can be activated independently of PDK1. Mass spectrometry analysis of RSK1, Aktl, S6K1 and MSK1 immunopurified from TPCK-treated cells identified TPCK adducts on cysteines located in conserved activation loop Phenylalanine-Cysteine (Phe-Cys) motifs. Mutational analysis of the Phe-Cys residues conferred partial TPCK resistance. These studies elucidate a primary mechanism by which TPCK inhibits several AGC kinases, inviting consideration of TPCK-like compounds in chemotherapy given their potential for broad control of cellular growth, proliferation and survival.     

Morphometric and genetic differentiation in isolated populations of the endangered Mesoamerican stingless bee <Emphasis Type="Italic">Melipona yucatanica</Emphasis> (Hymenoptera: Apoidea) suggest the existence of a two species complex

The stingless bee Melipona yucatanica is a rare species only found in preserved forests across Mesoamerica. Morphometric and molecular analyses (DNA barcoding of the cytochrome oxidase (cox1) and microsatellites) were combined to characterize and compare populations from Mexico and Guatemala. We aim to test the hypothesis predicting that populations from these two geographic regions could be considered as distinct taxonomic units. Morphometric analyses revealed geographic differences, Guatemalan bees being larger than Mexican specimens. Bayesian analyses of the mitochondrial cox1 region and the microsatellite loci demonstrated that M. yucatanica form two clades corresponding to the Mexican and Guatemalan populations. These results suggest that M. yucatanica from Mexico and Guatemala could represent two distinct species. However, more studies are needed on their ecology and behavior to determine the possibility of gene flow between them.     

Effect of smoking on circulating angiogenic factors in high risk pregnancies

Objective

Changes in maternal concentrations of the anti-angiogenic factors, soluble fms-like tyrosine kinase 1 (sFlt1) and soluble endoglin (sEng), and the pro-angiogenic placental growth factor (PlGF) precede the development of preeclampsia in healthy women. The risk of preeclampsia is reduced in women who smoke during pregnancy. The objective of this study was to investigate whether smoking affects concentrations of angiogenic factors (sFlt1, PlGF, and sEng) in women at high risk for developing preeclampsia.

Study Design

We performed a secondary analysis of serum samples from 993 high-risk women (chronic hypertension, diabetes, multifetal gestation, and previous preeclampsia) in a preeclampsia prevention trial. sFlt1, sEng and PlGF were measured in serum samples obtained at study entry, which was prior to initiation of aspirin (median 19.0 weeks'' [interquartile range of 16.0–22.6 weeks'']). Smoking status was determined by self-report.

Results

sFlt1 was not significantly different in smokers from any high-risk groups compared to their nonsmoking counterparts. PlGF was higher among smokers compared to nonsmokers among diabetic women (142.7 [77.4–337.3] vs 95.9 [48.5–180.7] pg/ml, p = 0.005) and women with a history of preeclampsia (252.2 [137.1–486.0] vs 152.2 [73.6–253.7] pg/ml, p = 0.001). sEng was lower in smokers with multifetal gestations (5.8 [4.6–6.5] vs 6.8 [5.5–8.7] ng/ml, p = 0.002) and trended lower among smokers with diabetes (4.9 [3.8–5.6] vs 5.3 [4.3–6.3] ng/ml, p = 0.05). Smoking was not associated with a lower incidence of preeclampsia in any of these groups.

Conclusions

In certain high-risk groups, smoking is associated with changes in the concentrations of these factors towards a pro-angiogenic direction during early pregnancy; however, there was no apparent association between smoking and the development of preeclampsia in our cohort.     

A metagenomic analysis of pandemic influenza A (2009 H1N1) infection in patients from North America

Although metagenomics has been previously employed for pathogen discovery, its cost and complexity have prevented its use as a practical front-line diagnostic for unknown infectious diseases. Here we demonstrate the utility of two metagenomics-based strategies, a pan-viral microarray (Virochip) and deep sequencing, for the identification and characterization of 2009 pandemic H1N1 influenza A virus. Using nasopharyngeal swabs collected during the earliest stages of the pandemic in Mexico, Canada, and the United States (n = 17), the Virochip was able to detect a novel virus most closely related to swine influenza viruses without a priori information. Deep sequencing yielded reads corresponding to 2009 H1N1 influenza in each sample (percentage of aligned sequences corresponding to 2009 H1N1 ranging from 0.0011% to 10.9%), with up to 97% coverage of the influenza genome in one sample. Detection of 2009 H1N1 by deep sequencing was possible even at titers near the limits of detection for specific RT-PCR, and the percentage of sequence reads was linearly correlated with virus titer. Deep sequencing also provided insights into the upper respiratory microbiota and host gene expression in response to 2009 H1N1 infection. An unbiased analysis combining sequence data from all 17 outbreak samples revealed that 90% of the 2009 H1N1 genome could be assembled de novo without the use of any reference sequence, including assembly of several near full-length genomic segments. These results indicate that a streamlined metagenomics detection strategy can potentially replace the multiple conventional diagnostic tests required to investigate an outbreak of a novel pathogen, and provide a blueprint for comprehensive diagnosis of unexplained acute illnesses or outbreaks in clinical and public health settings.     

Combining two Meishan F2 crosses improves the detection of QTL on pig chromosomes 2, 4 and 6

Background

In pig, a number of experiments have been set up to identify QTL and a multitude of chromosomal regions harbouring genes influencing traits of interest have been identified. However, the mapping resolution remains limited in most cases and the detected QTL are rather inaccurately located. Mapping accuracy can be improved by increasing the number of phenotyped and genotyped individuals and/or the number of informative markers. An alternative approach to overcome the limited power of individual studies is to combine data from two or more independent designs.

Methods

In the present study we report a combined analysis of two independent design (a French and a Dutch F2 experimental designs), with 2000 F2 individuals. The purpose was to further map QTL for growth and fatness on pig chromosomes 2, 4 and 6. Using QTL-map software, uni- and multiple-QTL detection analyses were applied separately on the two pedigrees and then on the combination of the two pedigrees.

Results

Joint analyses of the combined pedigree provided (1) greater significance of shared QTL, (2) exclusion of false suggestive QTL and (3) greater mapping precision for shared QTL.

Conclusions

Combining two Meishan x European breeds F2 pedigrees improved the mapping of QTL compared to analysing pedigrees separately. Our work was facilitated by the access to raw phenotypic data and DNA of animals from both pedigrees and the combination of the two designs with the addition of new markers allowed us to fine map QTL without phenotyping additional animals.     

Image-based pooled whole-genome CRISPRi screening for subcellular phenotypes

Genome-wide CRISPR screens have transformed our ability to systematically interrogate human gene function, but are currently limited to a subset of cellular phenotypes. We report a novel pooled screening approach for a wider range of cellular and subtle subcellular phenotypes. Machine learning and convolutional neural network models are trained on the subcellular phenotype to be queried. Genome-wide screening then utilizes cells stably expressing dCas9-KRAB (CRISPRi), photoactivatable fluorescent protein (PA-mCherry), and a lentiviral guide RNA (gRNA) pool. Cells are screened by using microscopy and classified by artificial intelligence (AI) algorithms, which precisely identify the genetically altered phenotype. Cells with the phenotype of interest are photoactivated and isolated via flow cytometry, and the gRNAs are identified by sequencing. A proof-of-concept screen accurately identified PINK1 as essential for Parkin recruitment to mitochondria. A genome-wide screen identified factors mediating TFEB relocation from the nucleus to the cytosol upon prolonged starvation. Twenty-one of the 64 hits called by the neural network model were independently validated, revealing new effectors of TFEB subcellular localization. This approach, AI-photoswitchable screening (AI-PS), offers a novel screening platform capable of classifying a broad range of mammalian subcellular morphologies, an approach largely unattainable with current methodologies at genome-wide scale.     

The Microbial Spectrum of Neonatal Sepsis in Uganda: Recovery of Culturable Bacteria in Mother-Infant Pairs

Neonatal sepsis in the developing world is incompletely characterized. We seek to characterize the microbial spectrum involved in sepsis and determine the role of maternal transmission by comparing organisms that can be cultured from septic newborn infants and their mothers. From 80 consecutive mother-infant pairs meeting clinical criteria for neonatal sepsis, we collected infant blood and spinal fluid, and maternal blood and vaginal specimens. Identifiable bacteria were recovered from the blood in 32.5% of infants, and from 2.5% of cerebrospinal fluid cultures, for a total of 35% recoverable putative causative agents. Bacteria recovered from vaginal specimens were not concordant with those recovered from infants. Similarly there was no concordance of bacteria recovered from blood and cerebrospinal fluid. We conclude that relying on traditional bacterial culture techniques does not adequately delineate the role of maternal versus environmental sources of neonatal sepsis in this setting. More sensitive molecular approaches will be needed to properly characterize the maternal and environmental microbial community involved in neonatal sepsis in such developing countries.     

An NMR Conformational Analysis of Cyclic Bradykinin Mimics. Evidence for a β-Turn

Abstract

A detailed NMR study is carried out in acetonitrile/water solutions on three novel cyclic bradykinin antagonist analogues, BKM-824, BKM-870, and BKM-872, to examine their solution structures, and to correlate the structures with bradykinin antagonist and anti-cancer activities. The solution structures of the cyclic peptides are correlated with the structural data for known linear bradykinin antagonists. The sequences are: BKM-824 c[Ava-Igl-Ser-DF5F-Oic- Arg] where Ava is 5-aminovaleric acid, Igl is α-(2-indanyl)glycine, F5F is pentafluorophenylalanine, and Oic is (2S,3aS,7aS)-octahydroindole-2-carboxylic acid; BKM-870; c[DArg-Arg-Add-DF5F-Oic-Arg] where Add is 12-aminododecanoic acid; and BKM-872; c[DArg-Arg-Eac-Ser-DF5F-Oic-Arg] where Eac is 6-aminocaproic acid. BKM-824 was the only peptide within this series that possessed a discernable solution structure. The NMR data indicate the presence of a type I β-turn between residues F5F⁴ and Ava¹, a C-terminal-like end. Molecular dynamics calculations show that a type I β-turn from DF5F⁴ to Ava¹ does exist although the turn was somewhat distorted. This result differs from the structures seen in linear bradykinin antagonists, which usually possess a type II II′β-turn at the C-terminal end and the presence of a defined turn is correlated with bradykinin antagonist activity. There is no solution structure for BKM-870 and BKM-872 but a correlation between the primary sequence Arg^terminal-DArg¹-Arg²-long chain aliphatic amino acid and anti-cancer activity is evident.     

Solution structure of UIM and interaction of tandem ubiquitin binding domains in STAM1 with ubiquitin

STAM1 and Hrs are the components of ESCRT-0 complex for lysosomal degradation of membrane proteins is composed of STAM1 Hrs and has multiple ubiquitin binding domains. Here, the solution structure of STAM1 UIM, one of the ubiquitin binding motif, was determined by NMR spectroscopy. The structure of UIM adopts an α-helix with amphipathic nature. The central hydrophobic residues in UIM provides the binding surface for ubiquitin binding and are flanked with positively and negatively charged residues on both sides. The docking model of STAM1 UIM-ubiquitin complex is suggested. In NMR and ITC experiments with the specifically designed mutant proteins, we investigated the ubiquitin interaction of tandem ubiquitin binding domains from STAM1. The ubiquitin binding affinity of the VHS domain and UIM in STAM1 was 52.4 and 94.9 μM, and 1.5 and 2.2 fold increased, respectively, than the value obtained from the isolated domain or peptide. The binding affinities here would be more physiologically relevant and provide more precise understanding in ESCRT pathway of lysosomal degradation.     

Melanoblast proliferation dynamics during mouse embryonic development. Modeling and validation

In this paper, we are looking for mathematical modeling of mouse embryonic melanoblast proliferation dynamics, taking into account, the expression level of β‐catenin. This protein plays an important role into the whole signal pathway process. Different assumptions on some unobservable features lead to different candidate models. From real data measured, from biological experiments and from a priori biological knowledge, it was able to validate or invalidate some of the candidate models. Data assimilation and parameter identification allowed us to derive a mathematical model that is in very good agreement with biological data. As a result, the produced model can give tracks for biologists into their biological investigations and experimental evidence. Another interest is the use of this model for robust hidden parameter identification like double times or number of founder melanoblasts.