Cassava is a well-known starchy root crop utilized for food, feed and biofuel production. However, the comprehension underlying the process of starch production in cassava is not yet available.

Long non-coding RNAs (lncRNAs) play important roles in the regulation of complex cellular processes, including transcriptional and post-transcriptional regulation of gene expression relevant for development and stress response, among others. Compared to other important crops, there is limited knowledge of cassava lncRNAs and their roles in abiotic stress adaptation. In this study, we performed a genome-wide study of ncRNAs in cassava, integrating genomics- and transcriptomics-based approaches. In total, 56,840 putative ncRNAs were identified, and approximately half the number were verified using expression data or previously known ncRNAs. Among these were 2229 potential novel lncRNA transcripts with unmatched sequences, 250 of which were differentially expressed in cold or drought conditions, relative to controls. We showed that lncRNAs might be involved in post-transcriptional regulation of stress-induced transcription factors (TFs) such as zinc-finger, WRKY, and nuclear factor Y gene families. These findings deepened our knowledge of cassava lncRNAs and shed light on their stress-responsive roles.

Analysis of metabolic flux was used for system level assessment of carbon partitioning in Kasetsart 50 (KU50) and Hanatee (HN) cassava cultivars to understand the metabolic routes for their distinct phenotypes. First, the constraint-based metabolic model of cassava storage roots, rMeCBM, was developed based on the carbon assimilation pathway of cassava. Following the subcellular compartmentalization and curation to ensure full network connectivity and reflect the complexity of eukaryotic cells, cultivar specific data on sucrose uptake and biomass synthesis were input, and rMeCBM model was used to simulate storage root growth in KU50 and HN. Results showed that rMeCBM-KU50 and rMeCBM-HN models well imitated the storage root growth. The flux-sum analysis revealed that both cultivars utilized different metabolic precursors to produce energy in plastid. More carbon flux was invested in the syntheses of carbohydrates and amino acids in KU50 than in HN. Also, KU50 utilized less flux for respiration and less energy to synthesize one gram of dry storage root. These results may disclose metabolic potential of KU50 underlying its higher storage root and starch yield over HN. Moreover, sensitivity analysis indicated the robustness of rMeCBM model. The knowledge gained might be useful for identifying engineering targets for cassava yield improvement.

Cassava storage roots (SR) are an important source of food energy and raw material for a wide range of applications. Understanding SR initiation and the associated regulation is critical to boosting tuber yield in cassava. Decades of transcriptome studies have identified key regulators relevant to SR formation, transcriptional regulation and sugar metabolism. However, there remain uncertainties over the roles of the regulators in modulating the onset of SR development owing to the limitation of the widely applied differential gene expression analysis. Here, we aimed to investigate the regulation underlying the transition from fibrous (FR) to SR based on Dynamic Network Biomarker (DNB) analysis. Gene expression analysis during cassava root initiation showed the transition period to SR happened in FR during 8 weeks after planting (FR8). Ninety-nine DNB genes associated with SR initiation and development were identified. Interestingly, the role of trehalose metabolism, especially trehalase1 (TRE1), in modulating metabolites abundance and coordinating regulatory signaling and carbon substrate availability via the connection of transcriptional regulation and sugar metabolism was highlighted. The results agree with the associated DNB characters of TRE1 reported in other transcriptome studies of cassava SR initiation and Attre1 loss of function in literature. The findings help fill the knowledge gap regarding the regulation underlying cassava SR initiation.

Microbial fuel cells (MFCs) are innovative eco-friendly technologies that advance a circular economy by enabling the conversion of both organic and inorganic substances in wastewater to electricity. While conceptually promising, there are lingering questions regarding the performance and stability of MFCs in real industrial settings. To address this research gap, we investigated the influence of specific operational settings, regarding the hydraulic retention time (HRT) and organic loading rate (OLR) on the performance of MFCs used for treating sulfide-rich wastewater from a canned pineapple factory. Experiments were performed at varying hydraulic retention times (2 days and 4 days) during both low and high seasonal production. Through optimization, we achieved a current density generation of 47±15 mA/m², a COD removal efficiency of 91±9%, and a sulfide removal efficiency of 86±10%. Microbiome analysis revealed improved MFC performance when there was a substantial presence of electrogenic bacteria, sulfide-oxidizing bacteria, and methanotrophs, alongside a reduced abundance of sulfate-reducing bacteria and methanogens. In conclusion, we recommend the following operational guidelines for applying MFCs in industrial wastewater treatment: (i) Careful selection of the microbial inoculum, as this step significantly influences the composition of the MFC microbial community and its overall performance. (ii) Initiating MFC operation with an appropriate OLR is essential. This helps in establishing an effective and adaptable microbial community within the MFCs, which can be beneficial when facing variations in OLR due to seasonal production changes. (iii) Identifying and maintaining MFC-supporting microbes, including those identified in this study, should be a priority. Keeping these microbes as an integral part of the system’s microbial composition throughout the operation enhances and stabilizes MFC performance.