Identification and Functional Prediction of Long Intergenic Non-coding RNAs Related to Subcutaneous Adipose Development in Pigs

An increasing number of studies have shown that long intergenic non-coding RNAs (lincRNAs) are a very important class of non-coding RNAs that plays a vital role in many biological processes. Adipose tissue is an important place for storing energy, but few studies on lincRNAs were related to pig subcutaneous fat development. Here, we used published RNA-seq data from subcutaneous adipose tissue of Italian Large White pigs and identified 252 putative lincRNAs, wherein 34 were unannotated. These lincRNAs had relatively shorter length, lower number of exons, and lower expression level compared with protein-coding transcripts. Gene ontology and pathway analysis indicated that the adjacent genes of lincRNAs were involved in lipid metabolism. In addition, differentially expressed lincRNAs (DELs) between low and high backfat thickness pigs were identified. Through the detection of quantitative trait locus (QTL), DELs were mainly located in QTLs related to adipose development. Based on the expression correlation of DEL genes and their differentially expressed potential target genes, we constructed a co-expression network and a potential pathway of DEL’s effect on lipid metabolism. Our study identified and analyzed lincRNAs in subcutaneous adipose tissue, and results suggested that lincRNAs may be involved in the regulation of subcutaneous fat development. Our findings provided new insights into the biological function of porcine lincRNAs

Transcriptome Analysis Suggests the Roles of Long Intergenic Non-coding RNAs in the Growth Performance of Weaned Piglets

Long intergenic non-coding RNAs (lincRNAs) have been considered to play a key regulatory role in various biological processes. An increasing number of studies have utilized transcriptome analysis to obtain lincRNAs with functions related to cancer, but lincRNAs affecting growth rates in weaned piglets are rarely described. Although lincRNAs have been systematically identified in various mouse tissues and cell lines, studies of lincRNA in pigs remain rare. Therefore, identifying and characterizing novel lincRNAs affecting the growth performance of weaned piglets is of great importance. Here, we reconstructed 101,988 lincRNA transcripts and identified 1,078 lincRNAs in two groups of longissimus dorsi muscle (LDM) and subcutaneous fat (SF) based on published RNA-seq datasets. These lincRNAs exhibit typical characteristics, such as shorter lengths and lower expression relative to protein-encoding genes. Gene ontology analysis revealed that some lincRNAs could be involved in weaned piglet related processes, such as insulin resistance and the AMPK signaling pathway. We also compared the positional relationship between differentially expressed lincRNAs (DELs) and quantitative trait loci (QTL) and found that some of DELs may play an important role in piglet growth and development. Our work details part of the lincRNAs that may affect the growth performance of weaned piglets and promotes future studies of lincRNAs for molecular-assisted development in weaned piglets

Developing a proteomics pipeline for characterisation of a synthetic microbial co-culture

Inspired by microbial communities can undertake more complex tasks than pure cell cultures and can achieve continuous production of valuable products, an increasingly number of attempts have been made to grow artificial or synthetic microbial communities composed of designated species. However, detailed understanding of their communications and stability is often insufficient. A detailed understanding of the composition and dynamics of microbial communities is necessary to gain fundamental insights into the interactions among species. In this project, a synthetic microbial co-culture system was constructed using genetically engineered strains of photosynthetic cyanobacterium Synechococcus elongatus cscB/SPS and nitrogen-fixing bacterium Azotobacter vinelandii nifL, in which the sucrose produced from S. elongatus cscB/SPS would be the carbon source for A. vinelandii nifL and the ammonium produced from A. vinelandii nifL would be the nitrogen source for S. elongatus cscB/SPS. This synthetic microbial co-culture can convert sunlight, carbondioxide, and atmospheric nitrogen into desired bio-product polyhydroxybutyrate (PHB). Quantitative proteomics can provide valuable insights into how microbial strains adapt to changing conditions. However, current workflows and methodologies are not suitable for simple artificial co-culture systems where strain ratios are dynamic. Therefore, a mass spectrometry-based label-free shotgun proteomics workflow was established for the analysis of the composition and changes of the synthetic microbial co-culture proteome. Furthermore, a new normalization method was proposed, named “LFQRatio”, to reflect the relative contributions of the two distinct cell types emerging from the cell ratio changes during co-cultivation and minimise the impact of cell number changes for proteome quantification in microbial co-culture. Lastly, comparative proteomics was performed to analyse the protein changes of A. vinelandii nifL and S. elongatus cscB/SPS in the synthetic co-culture, showing higher relative abundance of proteins in nitrogen fixation and photosynthesis pathways, which is evidence of the cross-feeding between the two members. In addition, co-culture proteomics changes over time were studied, demonstrating some interactions between co-cultures, including general carbon metabolism, two-component system, bacterial chemotaxis, etc. The proteomics results reveal potential targets for optimisation to keep the synthetic microbial co-culture healthier and longer-lived

Exploring the combination and heterogeneity of ecosystem services bundles in the Beijing-Tianjin Sandstorm Source Control Project

The relationships among ecosystem services (ESs) and their spatiotemporal dynamics plays an essential role in ESs management. However, it is difficult to characterize the spatial composition of ecosystem services bundles (ESB), clarify the complex relationships and their driving forces. This study estimated 6 specific ESs of Beijing-Tianjin Sandstorm Source Control Project (BTSSCP) based on related models, using conjunction operations identified ESB, finally explored the trade-offs and synergies between ESs within each ESB, and furtherly suggested different management zones in terms of ESB types. The results indicated the values of all six key ESs have improved from 2000 to 2015, and shown a decreasing trend from the southeast to the northwest accompanied by expansion trend of the high value region. Additionally, ESB dominated by sand-fixing service were primarily distributed in the southwest and showed a trend of continuous and significant expansion from southwest to northeast during 2000–2015. And, wind speed, soil types, slope, vegetation types and population density are the main driving factors of ESB changes. What’s more, trade-offs and synergies among ESs appears the characteristics of spatial heterogeneity, especially between sand-fixing service and Net primary productivity, which presenting synergistic promotion relationship in bundles 1 and 2, while significant trade-offs in bundles 3 and 4. Finally, we divided BTSSCP into three zones—key improvement zone, ecological conservation zone, and integrated optimization zone based on ESB as per the regional sand-fixing capacity, enhancement potential and the relationship between ESs, and proposed specific suggestions for management in various ESB, which are beneficial to regional sustainable development and appropriate management

MEG3 Promotes Differentiation of Porcine Satellite Cells by Sponging miR-423-5p to Relieve Inhibiting Effect on SRF

Although thousands of long noncoding RNAs (lncRNAs) have been identified in porcine growth and development, the regulation mechanisms of functional lncRNAs have not been well explored. In this study, using 5′- and 3′-rapid amplification of cDNA ends (RACE) assays, we obtained two different variants of lncRNA maternally expressed gene 3 (MEG3), namely, MEG3 v1 and MEG3 v2, that were both highly expressed in porcine skeletal muscle and in the early stage of the differentiation of porcine satellite cells. Moreover, we identified the core transcript MEG3 v2. Functional analyses showed that MEG3 overexpression could effectively arrest myoblasts in the G1 phase, inhibit DNA replication, and promote myoblast differentiation, whereas MEG3 knockdown resulted in the opposite effects. Interestingly, the expression of serum response factor (SRF), a crucial transcription factor for myogenesis process, remarkably increased and decreased in mRNA and protein levels with the respective overexpression and knockdown of MEG3. Dual luciferase reporter assay showed that MEG3 could attenuate the decrease of luciferase activity of SRF induced by miR-423-5p in a dose-dependent manner. MEG3 overexpression could relieve the inhibitory effect on SRF and myoblast differentiation induced by miR-423-5p. In addition, results of RNA immunoprecipitation analysis suggested that MEG3 could act as a ceRNA for miR-423-5p. Our findings initially established a novel connection among MEG3, miR-423-5p, and SRF in porcine satellite cell differentiation. This novel role of MEG3 may shed new light on understanding of molecular regulation of lncRNA in porcine myogenesis

Systematic Engineering for Improved Carbon Economy in the Biosynthesis of Polyhydroxyalkanoates and Isoprenoids

With the rapid development of synthetic biology and metabolic engineering, a broad range of biochemicals can be biosynthesized, which include polyhydroxyalkanoates and isoprenoids. However, some of the bio-approaches in chemical synthesis have just started to be applied outside of laboratory settings, and many require considerable efforts to achieve economies of scale. One of the often-seen barriers is the low yield and productivity, which leads to higher unit cost and unit capital investment for the bioconversion process. In general, higher carbon economy (less carbon wastes during conversion process from biomass to objective bio-based chemicals) will result in higher bioconversion yield, which results in less waste being generated during the process. To achieve this goal, diversified strategies have been applied; matured strategies include pathway engineering to block competitive pathways, enzyme engineering to enhance the activities of enzymes, and process optimization to improve biomass/carbon yield. In this review, we analyze the impact of carbon sources from different types of biomass on the yield of bio-based chemicals (especially for polyhydroxyalkanoates and isoprenoids). Moreover, we summarize the traditional strategies for improving carbon economy during the bioconversion process and introduce the updated techniques in building up non-natural carbon pathways, which demonstrate higher carbon economies than their natural counterparts

LFQRatio: A Normalization Method to Decipher Quantitative Proteome Changes in Microbial Coculture Systems

The value of synthetic microbial communities in biotechnology is gaining traction due to their ability to undertake more complex metabolic tasks than monocultures. However, a thorough understanding of strain interactions, productivity, and stability is often required to optimize growth and scale up cultivation. Quantitative proteomics can provide valuable insights into how microbial strains adapt to changing conditions in biomanufacturing. However, current workflows and methodologies are not suitable for simple artificial coculture systems where strain ratios are dynamic. Here, we established a workflow for coculture proteomics using an exemplar system containing two members, Azotobacter vinelandii and Synechococcus elongatus. Factors affecting the quantitative accuracy of coculture proteomics were investigated, including peptide physicochemical characteristics such as molecular weight, isoelectric point, hydrophobicity, and dynamic range as well as factors relating to protein identification such as varying proteome size and shared peptides between species. Different quantification methods based on spectral counts and intensity were evaluated at the protein and cell level. We propose a new normalization method, named “LFQRatio”, to reflect the relative contributions of two distinct cell types emerging from cell ratio changes during cocultivation. LFQRatio can be applied to real coculture proteomics experiments, providing accurate insights into quantitative proteome changes in each strain