Further results on the survival of a gene represented in a founder population

This paper is concerned with gene survival in a population which may increase without density dependence according to a generalization of the Moran model for haploid individuals. A selective advantage to one allele and the possibility of differential reproductive rates are allowed. Simple conditions are given for ultimate homozygosity to be certain and for the possibility of ultimate polymorphism. The results complement and extend those of Heyde (1981, 1982).     

fimA-folD genes linkage in Salmonella identifies a putative junctional site of chromosomal rearrangement in the enterobacterial genome

Abstract Analysis of the Salmonella chromosomal region located upstream of the fimA gene (coding for the major type 1 fimbrial subunit) showed a close linkage of this gene to the folD gene (coding for the enzyme 5,10-methylenetetrahydrofolate dehydrogenase/5, 10-methenyltetrahydrofolate cyclohydrolase), indicating that the fim gene cluster of Salmonella , unlike that of Escherichia coli , has no regulatory genes located upstream of fimA and apparently terminates with this gene. The respective locations of the fim and folD genes in the E. coli and Salmonella genetic maps suggests that the fimA-folD intergenic region of Salmonella encompasses a junctional site of a genetic rearrangement that probably originated from the different chromosomal location of the fim genes in these species.     

Polyplex-embedding in polyelectrolyte multilayers for gene delivery

In this work, incorporation of plasmid DNA, pre-complexed with PEI, into polyelectrolyte multilayers has been studied to further develop platforms for local gene delivery. Polyplex embedding in synthetic and naturally degradable architectures was efficient for transfection of human hepato-cellular carcinoma cells.     

Transposition-mediated transcriptional overexpression as a mechanism of insecticide resistance

It has been proposed that amplification of genes for esterase that provide resistance to insecticides may originate from transposition events. To test this hypothesis, we have constructed a minigene coding for a soluble acetylcholinesterase under the control of a nontissue-specific promoter (hsp70). When introduced into Drosophila, the gene is expressed in all tissues and the extra acetylcholinesterase produced confers a low level of insecticide resistance (twofold). The minigene was mobilized by crossing the initial transformant with a strain providing a source of P-element transposase. After 34 generations of exposure to the organophosphate parathion, we obtained a strain with a higher resistance (fivefold). This strain had only one extra Ace gene, which overexpressed acetylcholinesterase. Thus, following transposition, resistance resulted from the overexpression of a single copy of the gene and not from gene amplification. Received: 9 August 1996 / Accepted: 27 May 1997     

Transfer and expression of the cryIVB and cryIVD genes of Bacillus thuringiensis subsp. israelensis in Bacillus sphaericus 2297

Abstract The genes encoding the CryIVB and CryIVD crystal polypeptides of B. thuringiensis subsp. israelensis were cloned indepently on a stable shuttle vector, and transfered into B. sphaericus 2297. Recombinant cells expressed the B. thuringiensis toxins during sporulation and were shown to be toxic to Aedes aegypti fourth instar larvae, whereas the parental strain was not.     

Multiomic Metabolic Enrichment Network Analysis Reveals Metabolite–Protein Physical Interaction Subnetworks Altered in Cancer

Metabolism is recognized as an important driver of cancer progression and other complex diseases, but global metabolite profiling remains a challenge. Protein expression profiling is often a poor proxy since existing pathway enrichment models provide an incomplete mapping between the proteome and metabolism. To overcome these gaps, we introduce multiomic metabolic enrichment network analysis (MOMENTA), an integrative multiomic data analysis framework for more accurately deducing metabolic pathway changes from proteomics data alone in a gene set analysis context by leveraging protein interaction networks to extend annotated metabolic models. We apply MOMENTA to proteomic data from diverse cancer cell lines and human tumors to demonstrate its utility at revealing variation in metabolic pathway activity across cancer types, which we verify using independent metabolomics measurements. The novel metabolic networks we uncover in breast cancer and other tumors are linked to clinical outcomes, underscoring the pathophysiological relevance of the findings.     

Structure-based protein design with deep learning

Since the first revelation of proteins functioning as macromolecular machines through their three dimensional structures, researchers have been intrigued by the marvelous ways the biochemical processes are carried out by proteins. The aspiration to understand protein structures has fueled extensive efforts across different scientific disciplines. In recent years, it has been demonstrated that proteins with new functionality or shapes can be designed via structure-based modeling methods, and the design strategies have combined all available information — but largely piece-by-piece — from sequence derived statistics to the detailed atomic-level modeling of chemical interactions. Despite the significant progress, incorporating data-derived approaches through the use of deep learning methods can be a game changer. In this review, we summarize current progress, compare the arc of developing the deep learning approaches with the conventional methods, and describe the motivation and concepts behind current strategies that may lead to potential future opportunities.     

A comparative Proteomics Analysis Identified Differentially Expressed Proteins in Pancreatic Cancer–Associated Stellate Cell Small Extracellular Vesicles

Human pancreatic stellate cells (HPSCs) are an essential stromal component and mediators of pancreatic ductal adenocarcinoma (PDAC) progression. Small extracellular vesicles (sEVs) are membrane-enclosed nanoparticles involved in cell-to-cell communications and are released from stromal cells within PDAC. A detailed comparison of sEVs from normal pancreatic stellate cells (HPaStec) and from PDAC-associated stellate cells (HPSCs) remains a gap in our current knowledge regarding stellate cells and PDAC. We hypothesized there would be differences in sEVs secretion and protein expression that might contribute to PDAC biology. To test this hypothesis, we isolated sEVs using ultracentrifugation followed by characterization by electron microscopy and Nanoparticle Tracking Analysis. We report here our initial observations. First, HPSC cells derived from PDAC tumors secrete a higher volume of sEVs when compared to normal pancreatic stellate cells (HPaStec). Although our data revealed that both normal and tumor-derived sEVs demonstrated no significant biological effect on cancer cells, we observed efficient uptake of sEVs by both normal and cancer epithelial cells. Additionally, intact membrane-associated proteins on sEVs were essential for efficient uptake. We then compared sEV proteins isolated from HPSCs and HPaStecs cells using liquid chromatography–tandem mass spectrometry. Most of the 1481 protein groups identified were shared with the exosome database, ExoCarta. Eighty-seven protein groups were differentially expressed (selected by 2-fold difference and adjusted p value ≤0.05) between HPSC and HPaStec sEVs. Of note, HPSC sEVs contained dramatically more CSE1L (chromosome segregation 1–like protein), a described marker of poor prognosis in patients with pancreatic cancer. Based on our results, we have demonstrated unique populations of sEVs originating from stromal cells with PDAC and suggest that these are significant to cancer biology. Further studies should be undertaken to gain a deeper understanding that could drive novel therapy.     

Growth-induced mass flows in fungal networks

Cord-forming fungi form extensive networks that continuously adapt to maintain an efficient transport system. As osmotically driven water uptake is often distal from the tips, and aqueous fluids are incompressible, we propose that growth induces mass flows across the mycelium, whether or not there are intrahyphal concentration gradients. We imaged the temporal evolution of networks formed by Phanerochaete velutina, and at each stage calculated the unique set of currents that account for the observed changes in cord volume, while minimizing the work required to overcome viscous drag. Predicted speeds were in reasonable agreement with experimental data, and the pressure gradients needed to produce these flows are small. Furthermore, cords that were predicted to carry fast-moving or large currents were significantly more likely to increase in size than cords with slow-moving or small currents. The incompressibility of the fluids within fungi means there is a rapid global response to local fluid movements. Hence velocity of fluid flow is a local signal that conveys quasi-global information about the role of a cord within the mycelium. We suggest that fluid incompressibility and the coupling of growth and mass flow are critical physical features that enable the development of efficient, adaptive biological transport networks.