Three decades of listeriology through the prism of technological advances

Decades of breakthroughs resulting from cross feeding of microbiological research and technological innovation have promoted Listeria monocytogenes to the rank of model microorganism to study host–pathogen interactions. The extraordinary capacity of this bacterium to interfere with a vast array of host cellular processes uncovered new concepts in microbiology, cell biology and infection biology. Here, we review technological advances that revealed how bacteria and host interact in space and time at the molecular, cellular, tissue and whole body scales, ultimately revolutionising our understanding of Listeria pathogenesis. With the current bloom of multidisciplinary integrative approaches, Listeria entered a new microbiology era.     

Multifaceted roles of duckweed in aquatic phytoremediation and bioproducts synthesis

Duckweed (Lemnaceae) is a fast‐growing aquatic vascular plant. It has drawn an increasing attention worldwide due to its application in value‐added nutritional products and in sewage disposal. In particular, duckweed is a promising feedstock for bioenergy production. In this review, we summarized applications of duckweed from the following four aspects. Firstly, duckweed could utilize nitrogen, phosphorus, and inorganic nutrition in wastewater and reduces water eutrophication efficiently. During these processes, microorganisms play an important role in promoting duckweed growth and improving its tolerance to stresses. We also introduced our pilot‐scale test using duckweed for wastewater treatment and biomass production simultaneously. Secondly, its capability of fast accumulation of large amounts of starch makes duckweed a promising bioenergy feedstock, catering the currently increasing demand for bioethanol production. Pretreatment conditions prior to fermentation can be optimized to improve the conversion efficiency from starch to bioethanol. Furthermore, duckweed serves as an ideal source for food supply or animal feed because the composition of amino acids in duckweed is similar to that of whey protein, which is easily digested and assimilated by human and other animals. Finally, severing as a natural plant factory, duckweed has shown great potential in the production of pharmaceuticals and dietary supplements. With the surge of omics data and the development of Clustered Regularly Interspaced Short Palindromic Repeats technology, remodeling of the metabolic pathway in duckweed for synthetic biology study will be attainable in the future.     

The role of organic amendments to soil for crop protection: Induction of suppression of soilborne pathogens

Application of external organic inputs to soils can be considered as one of the most ancient strategies in agriculture, and it has been commonly used since the very beginning of human-based agricultural practices. During all this time, application of several organic matters to agricultural soils has demonstrated their benefit to plants and soils. Organic amendments have proved to be useful in recovering soil properties, improving soil quality and, in some cases, can be directly involved in providing beneficial effects to plants. All these obtained effects finally lead to an increase in crop protection and sustainability. One most expected effect caused by the application of organic amendments, is the suppression of a wide range of soilborne pathogens (mainly bacterial and fungal pathogens) due to the induction of physicochemical and biological changes in soils. In order to get insight into the nature of the induced soil suppression of soilborne plant pathogens, the analysis of the physical, chemical and the microbial changes, pointed to the key role of beneficial activities produced by soil microorganisms finally adapted to the environmental changes produced by the influence of organic amendments. As shown in the case studies reported here, participation of soil microbes specifically selected after organic amendment is crucial in the control of fungal soilborne diseases. Moreover, the development of “omics” approaches allowed these recent studies to go one step further, revealing the main actors involved in the induced soil suppressiveness and their activities. Thus “omics” techniques will help to understand the soil and its microbiome as a whole system, and to assign the important roles of its biological components.     

酒精发酵过程中酿酒酵母耐受环境胁迫的研究进展

提高酿酒酵母细胞耐受环境胁迫（高渗透压、高浓度酒精和高温）的能力对酒精工业生产具有重要的意义。对提高酿酒酵母耐受性的研究方法和策略的发展历程进行了综述。基因组学、转录组学和蛋白质组学等现代组学技术在这一领域的研究获得了广泛的应用。这些技术将提供期待的信息,去理性改造并获得更加耐受胁迫的工业酵母菌株。     

Driving Precision Medicine through Proteomics and Metabolomics - 12th Central and Eastern European Proteomic Conference (CEEPC), Bucharest,Romania

As Romanians prepared to celebrate 100 years of the '‘Great Unification of 1918?' which united all provinces into one Romania, the 12^th Central and Eastern European Proteomic Conference (CEEPC) jointly with the 39^th Anniversary of the Institute of Cellular Biology and Pathology '‘N. Simionescu’' (ICBP-NS), held their inaugural meeting at the Romanian Academy in Bucharest – a national forum of highest scientific recognition. With an exciting theme entitled, ‘Advances in Proteomics and Progress in Precision Medicine’, delegates gathered to debate Precision medicine’s revolution in diagnosis and treatment, which now accounts for predictive, preventative, and targeted treatment strategies with informed decisions according to individual’s unique clinical, molecular and genetic profile. Proteomics has a pivotal role to play in furthering precision health and medicine for the benefit of mankind. To this end, CEEPC continues to drive advances in proteomics, metabolomics, and diseases as well as raising awareness of pressing global humanitarian and health-care issues including mental health diseases, aging, chronic diseases, global epidemics and environmental issues. Today, CEEPC is a well-recognized major annual conference with a focused vision and a highly valued ideology as it continues to propagate scientific, medical and proteomic collaborations whilst expanding as more Eastern European countries prepare to join.     

Urinary D-serine level as a predictive biomarker for deterioration of renal function in patients with atherosclerotic risk factors

Background: D-serine, the enantiomer of L-serine, was identified in mammals 20?years ago. Although a close relationship between D-serine and renal dysfunction has been shown, the clinical implications of urinary D- and L-serine in humans are poorly understood. The aim of this study was to evaluate the relationship between urinary D- and L-serine with well-known renal biomarkers, and clarify the prognostic value of D- and L-serine for renal events.

Methods: This cross-sectional, prospective study included 65 patients with atherosclerotic risk factors, who were followed up for a median of 16?months. The primary endpoint was a composite of end-stage renal disease and a decline in estimated glomerular filtration rate (eGFR)?≥?25% from baseline.

Results: Urinary D-serine concentrations showed a better correlation with eGFR than did urinary L-serine, whereas neither urinary D- nor L-serine correlated with tubular markers such as urinary liver-type fatty acid-binding protein and N-acetyl-beta-D-glucosaminidase. A Cox regression analysis revealed that low urinary D-serine levels were significantly associated with the primary endpoint after adjusting for confounding factors (hazard ratio 12.60; 95% confidence interval, 3.49–45.51).

Conclusions: Urinary D-serine is associated with glomerular filtration and can be a prognostic biomarker of renal dysfunction in patients with atherosclerotic risk factors.     

Systems Metabolic Engineering Meets Machine Learning: A New Era for Data‐Driven Metabolic Engineering

The recent increase in high‐throughput capacity of ‘omics datasets combined with advances and interest in machine learning (ML) have created great opportunities for systems metabolic engineering. In this regard, data‐driven modeling methods have become increasingly valuable to metabolic strain design. In this review, the nature of ‘omics is discussed and a broad introduction to the ML algorithms combining these datasets into predictive models of metabolism and metabolic rewiring is provided. Next, this review highlights recent work in the literature that utilizes such data‐driven methods to inform various metabolic engineering efforts for different classes of application including product maximization, understanding and profiling phenotypes, de novo metabolic pathway design, and creation of robust system‐scale models for biotechnology. Overall, this review aims to highlight the potential and promise of using ML algorithms with metabolic engineering and systems biology related datasets.     

Molecular network strategy in multi-omics and mass spectrometry imaging

Human physiological activities and pathological changes arise from the coordinated interactions of multiple molecules. Mass spectrometry (MS)-based multi-omics and MS imaging (MSI)-based spatial omics are powerful methods used to investigate molecular information related to the phenotype of interest from homogenated or sliced samples, including the qualitative, relative quantitative and spatial distributions. Molecular network strategy provides efficient methods to help us understand and mine the biological patterns behind the phenotypic data. It illustrates and combines various relationships between molecules, and further performs the molecule identification and biological interpretation. Here, we describe the recent advances of network-based analysis and its applications for different biological processes, such as, obesity, central nervous system diseases, and environmental toxicology.