Effects of carbon sources, oxygenation and ethanol on the production of inulinase by Kluyveromyces marxianus YX01

Inulinase is one of the most important factors in consolidated bioprocessing, which combines enzyme production, inulin saccharification, and ethanol fermentation into a single process. In our study, inulinase production and cell growth of Kluyveromyces marxianus YX01 under different conditions were studied. Carbon source was shown to be significant on the production of inulinase, because the activity of inulinase was higher using inulin as a carbon source compared with glucose or fructose. The concentration of the carbon source had a repressive effect on the activity of inulinase. When the concentration was increased to 60 g/L, inulinase activity was only 50% compared with carbon source concentration of 20 g/L. Enzyme activity was also strongly influenced by aeration rate. It has been shown that the activity of inulinase and cell growth under anaerobic conditions were maintained at low levels, but aeration at 1.0 vvm (air volume/broth volume minute) led to higher activity. Inulinase activity per unit biomass was not significantly different under different aeration rates. Ethanol had a repressive effect on the cell growth. Cells ceased growing when the level of ethanol was greater than 9% (v/v), but ethanol did not affect the activity of secreted inulinase and the enzyme was stable at ethanol concentration up to 15%

Actual Measurement and Analysis on Microbial Contamination in Central Air Conditioning System at a Venue in Dalian, China

AbstractActual measurement and analysis were carried out on microbial contamination in central air conditioning system at a venue in Dalian. By studying the microbial contamination in two air handling units with different thermal environments, we found that the fungi and bacteria were common existing on the surface of filter, and the trend of cell density distribution was center > against the wall > corner; The microbial pollution associated in the dust and floating in the air was extremely serious. By comparing the two units, we observed that fungus concentration: Unit A > Unit B, and bacteria concentration: Unit A < Unit B,. And the candida spp. accounted for 80 percent of the sample in Unit A; while in Unit B the cladosporium spp. occupied up to 50%. At the end of the paper, according to the results of measurement and analysis, the methods of controlling microbial contamination in HVAC system have been proposed

Enhanced fermentative performance under stresses of multiple lignocellulose-derived inhibitors by overexpression of a typical 2-Cys peroxiredoxin from Kluyveromyces marxianus

Additional file 1: Figure S1. Construction of overexpressing vector and subsequent verification. a) The schematic of overexpressing vector containing KmTPX1 gene and its own promoter. b) PCR and restriction enzyme digestion verification with a band of 1042 bp. c) Relative abundance of KmTPX1 overexpression in SC-His medium by real-time quantitative PCR technology

Experimental and analytical studies on the pullout strength of round thread casing connections

497-503Pullout failure is one of the primary failure modes of API round thread casing connections. Make-up torque and thread tolerances are the two most important factors that can affect the pullout strength. In this paper, the pull-out failure process and mechanism are studied using the finite element analysis (FEA) method. In addition, the effects of make-up torque and thread tolerances on the pullout strength of API round thread connections are analyzed. The FEA results are validated through tension tests on a total of 34 pins and 17 couplings. The results show that pull-out failure initially occurs at the first and second teeth near the coupling end. At the same time, thread tolerances especially unmatched taper have notable effect on pullout strength. The tests show that higher make-up torque levels are beneficial to the pullout strength. Make-up torque 15~20% higher than the maximum API limit is recommended when round thread casing connections are used in oilfield

CRISPR-mediated genome editing in non-conventional yeasts for biotechnological applications

Abstract Non-conventional yeasts are playing important roles as cell factories for bioproduction of biofuels, food additives and proteins with outstanding natural characteristics. However, the precise genome editing is challenging in non-conventional yeasts due to lack of efficient genetic tools. In the past few years, CRISPR-based genome editing worked as a revolutionary tool for genetic engineering and showed great advantages in cellular metabolic engineering. Here, we review the current advances and barriers of CRISPR–Cas9 for genome editing in non-conventional yeasts and propose the possible solutions in enhancing its efficiency for precise genetic engineering

Advances in engineering methylotrophic yeast for biosynthesis of valuable chemicals from methanol

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MOESM1 of Synergistic effect of thioredoxin and its reductase from Kluyveromyces marxianus on enhanced tolerance to multiple lignocellulose-derived inhibitors

Additional file 1. Supplemental methods, tables and figures

Comparative Evaluation of State-of-the-Art Semantic Segmentation Networks for Long-Term Landslide Map Production

The production of long-term landslide maps (LAM) holds crucial importance in estimating landslide activity, vegetation disturbance, and regional stability. However, the availability of LAMs remains limited in many regions, despite the application of various machine-learning methods, deep-learning (DL) models, and ensemble strategies in landslide detection. While transfer learning is considered an effective approach to tackle this challenge, there has been limited exploration and comparison of the temporal transferability of state-of-the-art deep-learning models in the context of LAM production, leaving a significant gap in the research. In this study, an extensive series of tests was conducted to evaluate the temporal transferability of typical semantic segmentation models, specifically U-Net, U-Net 3+, and TransU-Net, using a 10-year landslide-inventory dataset located near the epicenter of the Wenchuan earthquake. The experiment results disclose the feasibility and limitations of implementing transfer-learning methods for LAM production, particularly when leveraging the power of U-Net 3+. Furthermore, following an assessment of the effects of varying data volumes, patch sizes, and time intervals, this study recommends appropriate settings for LAM production, emphasizing the balance between efficiency and production performance. The findings from this study can serve as a valuable reference for devising an efficient and reliable strategy for large-scale LAM production in landslide-prone regions

Engineering cofactor supply and recycling to drive phenolic acid biosynthesis in yeast

Advances in synthetic biology enable microbial hosts to synthesize valuable natural products in an efficient, cost-competitive and safe manner. However, current engineering endeavors focus mainly on enzyme engineering and pathway optimization, leaving the role of cofactors in microbial production of natural products and cofactor engineering largely ignored. Here we systematically engineered the supply and recycling of three cofactors (FADH2, S-adenosyl-l-methion and NADPH) in the yeast Saccharomyces cerevisiae, for high-level production of the phenolic acids caffeic acid and ferulic acid, the precursors of many pharmaceutical molecules. Tailored engineering strategies were developed for rewiring biosynthesis, compartmentalization and recycling of the cofactors, which enabled the highest production of caffeic acid (5.5 \ub1 0.2 g l−1) and ferulic acid (3.8 \ub1 0.3 g l−1) in microbial cell factories. These results demonstrate that cofactors play an essential role in driving natural product biosynthesis and the engineering strategies described here can be easily adopted for regulating the metabolism of other cofactors. [Figure not available: see fulltext.]