Screening of selected ageing-related proteins that extend chronological life span in yeast Saccharomyces cerevisiae.

Ageing-related proteins play various roles such as regulating cellular ageing, countering oxidative stress, and modulating signal transduction pathways amongst many others. Hundreds of ageing-related proteins have been identified, however the functions of most of these ageing-related proteins are not known. Here, we report the identification of proteins that extended yeast chronological life span (CLS) from a screen of ageing-related proteins. Three of the CLS-extending proteins, Ptc4, Zwf1, and Sme1, contributed to an overall higher survival percentage and shorter doubling time of yeast growth compared to the control. The CLS-extending proteins contributed to thermal and oxidative stress responses differently, suggesting different mechanisms of actions. The overexpression of Ptc4 or Zwf1 also promoted rapid cell proliferation during yeast growth, suggesting their involvement in cell division or growth pathways.

Identification of Tropical Plant Extracts That Extend Yeast Chronological Life Span.

Certain plant extracts (PEs) contain bioactive compounds that have antioxidant and lifespan-extending activities on organisms. These PEs play different roles in cellular processes, such as enhancing stress resistance and modulating longevity-defined signaling pathways that contribute to longevity. Here, we report the discovery of PEs that extended chronological life span (CLS) in budding yeast from a screen of 222 PEs. We identified two PEs, the leaf extracts of Manihot esculenta and Wodyetia bifurcata that extended CLS in a dose-dependent manner. The CLS-extending PEs also conferred oxidative stress tolerance, suggesting that these PEs might extend yeast CLS through the upregulation of stress response pathways.

Boswellia dalzielii-Mediated Silver Nanoparticles Inhibited Acute Myeloid Leukemia (AML) Kasumi-1 Cells by Inducing Cell Cycle Arrest.

BACKGROUND: Acute myeloid leukemia (AML) persists to be a major health problem especially among children as effective chemotherapy to combat the disease is yet to be available. Boswellia dalzielii is a well-known herb that is traditionally used for treatment and management of many diseases including degenerative diseases. In this study, silver nanoparticles were synthesized from the phytochemicals of B. dalzielii stem bark aqueous extract. The silver nanoparticles were characterized by carrying out Fourier Transform Infrared (FTIR) spectroscopy, Energy Filtered Scanning Electron Microscopy (FESEM), X-ray diffraction, and Dynamic Light Scattering (DLS) analyses. Antioxidant capacity of the nanoparticles was evaluated using 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay, and the antiproliferative effect of the nanoparticles on Kasumi-1 leukemia cells was investigated using PrestoBlue assay. Flow cytometry analysis was performed to observe the effect of the nanoparticles on the leukemia cell cycle progression. RESULTS: Our findings revealed that the synthesized silver nanoparticles were formed from electrons of the plant phytochemicals which include aromatic compounds, ethers, and alkynes. FESEM analysis revealed that the sizes of the nanoparticles range from 12 nm to 101 nm; however, DLS analysis estimated a larger average size of the nanoparticles (108.3 nm) because it measured the hydrodynamic radii of the nanoparticles. The zeta potential of the nanoparticles was -16 nm, and the XRD pattern of the nanoparticles has distinct peaks at 38.02°, 42.94°, 64.45°, 77.20°, and 81.47°, which is typical of face-centered cubic (fcc) structure of silver. The Trolox Equivalence Antioxidant Capacity (TEAC) of the nanoparticles was estimated to be 300.91 µM Trolox/mg silver nanoparticles. The nanoparticles inhibited Kasumi-1 cell proliferation. The half minimal inhibitory concentrations (IC50s) that inhibited Kasumi-1 cell proliferation are 49.5 µg/ml and 13.25 µg/ml at 48 and 72 hours, respectively. The nanoparticles induced cell cycle arrest in the Kasumi-1 cells at S (5% increase) and G2/M (3% increase) phases. CONCLUSION: The nanoparticles synthesized from the stem bark extract of B. dalzielii inhibit the growth of Kasumi-1 leukemia cells by activating cell cycle arrest; thus, they are potential antileukemic agents.

Inhibitory Effect of Eco-Friendly Naturally Synthesized Silver Nanoparticles from the Leaf Extract of Medicinal Detarium microcarpum Plant on Pancreatic and Cervical Cancer Cells.

BACKGROUND: Recently, nanoparticle synthesis by eco-friendly methods has received tremendous attention due to the method advantages and also because of the application of the nanoparticles in cancer research. Therefore, in this study, we synthesized silver nanoparticles from Detarium microcarpum leaf phytochemicals and evaluated its inhibitory effect on pancreatic and cervical cancer cells. MATERIALS AND METHODS: Silver nanoparticles (dAgNps) were synthesized by reacting phytochemicals of D. microcarpum leaves with silver nitrate for 12 hours. Cell viability assay was carried out to investigate the cytotoxic effect of dAgNps on HeLa and PANC-1 cells. RESULTS: Scanning electron microscopy (SEM) and transmission electron microscopy(TEM) results revealed the average sizes of dAgNps are 81 nm and 84 nm respectively. The x-ray diffraction (XRD) pattern of dAgNps was similar to that of face centered cubic(fcc) structure of silver as reported by joint committee on powder diffraction standards (JCPDS) and fourier-transform infrared spectroscopy (FTIR) analysis showed that some phytochemicals of D. microcarpum such as polyphenols and flavonoids were likely involved in the reduction of Ag+ to form nanoparticles. Finally, cell viability assay revealed dAgNps inhibited PANC-1 and HeLa cell proliferations with IC50 values of 84 and 31.5 µg/ml respectively. CONCLUSION: In conclusion, the synthesized nanoparticles from D. microcarpum leaves (dAgNps) have inhibitory effect on pancreatic and cervical cancer cells.

Comparison of microplate- and bottle-based methods to age yeast for chronological life span assays.

This study compared the chronological life span and survival of Saccharomyces cerevisiae aged in a microplate or bottle, under different aeration and calorie restriction conditions. Our data shows that limited aeration in the microplate-aged culture contributed to slower outgrowth but extended yeast CLS compared to the bottle-aged culture.

Assessment of three plastid DNA barcode markers for identification of Clinacanthus nutans (Acanthaceae).

This study was conducted to determine the feasibility of using three plastid DNA regions (matK, trnH-psbA, and rbcL) as DNA barcodes to identify the medicinal plant Clinacanthus nutans. In this study, C. nutans was collected at several different locations. Total genomic DNA was extracted, amplified by polymerase chain reaction (PCR), and sequenced using matK, trnH-psbA, and rbcL, primers. DNA sequences generated from PCR were submitted to the National Center for Biotechnology Information's (NCBI) GenBank. Identification of C. nutans was carried out using NCBI's Basic Local Alignment Search Tool (BLAST). The rbcL and trnH-psbA regions successfully identified C. nutans with sequencing rates of 100% through BLAST identification. Molecular Evolutionary Genetics Analysis (MEGA) 6.0 was used to analyze interspecific and intraspecific divergence of plastid DNA sequences. rbcL and matK exhibited the lowest average interspecific distance (0.0487 and 0.0963, respectively), whereas trnH-psbA exhibited the highest average interspecific distance (0.2029). The R package Spider revealed that trnH-psbA correctly identified Barcode of Life Data System (BOLD) 96%, best close match 79%, and near neighbor 100% of the species, compared to matK (BOLD 72%; best close match 64%; near neighbor 78%) and rbcL (BOLD 77%; best close match 62%; near neighbor 88%). These results indicate that trnH-psbA is very effective at identifying C. nutans, as it performed well in discriminating species in Acanthaceae.

Structure of polyhydroxyalkanoate (PHA) synthase PhaC from Chromobacterium sp. USM2, producing biodegradable plastics.

Polyhydroxyalkanoate (PHA) is a promising candidate for use as an alternative bioplastic to replace petroleum-based plastics. Our understanding of PHA synthase PhaC is poor due to the paucity of available three-dimensional structural information. Here we present a high-resolution crystal structure of the catalytic domain of PhaC from Chromobacterium sp. USM2, PhaC Cs -CAT. The structure shows that PhaC Cs -CAT forms an α/ß hydrolase fold comprising α/ß core and CAP subdomains. The active site containing Cys291, Asp447 and His477 is located at the bottom of the cavity, which is filled with water molecules and is covered by the partly disordered CAP subdomain. We designated our structure as the closed form, which is distinct from the recently reported catalytic domain from Cupriavidus necator (PhaC Cn -CAT). Structural comparison showed PhaC Cn -CAT adopting a partially open form maintaining a narrow substrate access channel to the active site, but no product egress. PhaC Cs -CAT forms a face-to-face dimer mediated by the CAP subdomains. This arrangement of the dimer is also distinct from that of the PhaC Cn -CAT dimer. These findings suggest that the CAP subdomain should undergo a conformational change during catalytic activity that involves rearrangement of the dimer to facilitate substrate entry and product formation and egress from the active site.

Evaluation of genetic diversity of Clinacanthus nutans (Acanthaceaea) using RAPD, ISSR and RAMP markers.

Three polymerase chain reaction (PCR) techniques were compared to analyse the genetic diversity of Clinacanthus nutans eight populations in the northern region of Peninsular Malaysia. The PCR techniques were random amplified polymorphic deoxyribonucleic acids (RAPD), inter-simple sequence repeats (ISSR) and random amplified microsatellite polymorphisms (RAMP). Leaf genomic DNA was PCR amplified using 17 RAPD, 8 ISSR and 136 RAMP primers . However, only 10 RAPD primers, 5 ISSR primers and 37 RAMP primers produced reproducible bands. The results were evaluated for polymorphic information content (PIC), marker index (MI) and resolving power (RP). The RAMP marker was the most useful marker compared to RAPD and ISSR markers because it showed the highest average value of PIC (0.25), MI (11.36) and RP (2.86). The genetic diversity showed a high percentage of polymorphism at the species level compared to the population level. Furthermore, analysis of molecular variance revealed that the genetic diversity was higher within populations, as compared to among populations of C. nutans. From the results, the RAMP technique was recommended for the analysis of genetic diversity of C. nutans.

A review of machine learning methods to predict the solubility of overexpressed recombinant proteins in Escherichia coli.

BACKGROUND: Over the last 20 years in biotechnology, the production of recombinant proteins has been a crucial bioprocess in both biopharmaceutical and research arena in terms of human health, scientific impact and economic volume. Although logical strategies of genetic engineering have been established, protein overexpression is still an art. In particular, heterologous expression is often hindered by low level of production and frequent fail due to opaque reasons. The problem is accentuated because there is no generic solution available to enhance heterologous overexpression. For a given protein, the extent of its solubility can indicate the quality of its function. Over 30% of synthesized proteins are not soluble. In certain experimental circumstances, including temperature, expression host, etc., protein solubility is a feature eventually defined by its sequence. Until now, numerous methods based on machine learning are proposed to predict the solubility of protein merely from its amino acid sequence. In spite of the 20 years of research on the matter, no comprehensive review is available on the published methods. RESULTS: This paper presents an extensive review of the existing models to predict protein solubility in Escherichia coli recombinant protein overexpression system. The models are investigated and compared regarding the datasets used, features, feature selection methods, machine learning techniques and accuracy of prediction. A discussion on the models is provided at the end. CONCLUSIONS: This study aims to investigate extensively the machine learning based methods to predict recombinant protein solubility, so as to offer a general as well as a detailed understanding for researches in the field. Some of the models present acceptable prediction performances and convenient user interfaces. These models can be considered as valuable tools to predict recombinant protein overexpression results before performing real laboratory experiments, thus saving labour, time and cost.