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Inborn errors of immunity (IEI) are genetic disorders with extensive clinical presentations. They can range from increased susceptibility to infections to significant immune dysregulation that results in immune impairment. While IEI cases are individually rare, they collectively represent a significant burden of disease, especially in developing countries such as South Africa, where infectious diseases like tuberculosis (TB) are endemic. This is particularly alarming considering that certain high penetrance mutations that cause IEI, such as Mendelian Susceptibility to Mycobacterial Disease (MSMD), put individuals at higher risk for developing TB and other mycobacterial diseases. MSMD patients in South Africa often present with different clinical phenotypes than those from the developed world, therefore complicating the identification of disease-associated variants in this setting with a high burden of infectious diseases. The lack of available data, limited resources, as well as variability in clinical phenotype are the reasons many MSMD cases remain undetected or misdiagnosed. This article highlights the challenges in diagnosing MSMD in South Africa and proposes the use of transcriptomic analysis as a means of potentially identifying dysregulated pathways in affected African populations., Competing Interests: The authors declare no conflict of interest.

Background: Host transcriptomic blood signatures have demonstrated diagnostic potential for tuberculosis (TB), requiring further validation across different geographical settings. Discriminating TB from other diseases with similar clinical manifestations is crucial for the development of an accurate immunodiagnostic tool. In this exploratory cohort study, we evaluated the performance of potential blood-based transcriptomic signatures in distinguishing TB disease from non-TB lower respiratory tract infections in hospitalised patients in a TB low-endemic country., Method: Quantitative real-time polymerase chain reaction qPCR) was used to evaluate 26 previously published genes in blood from 31 patients (14 TB and 17 lower respiratory tract infection cases) admitted to Oslo University Hospital in Norway. The diagnostic accuracies of differentially expressed genes were determined by receiver operating characteristic curves., Results: A significant difference ( p  < .01) in the age distribution was observed between patients with TB (mean age, 40 ± 15 years) and lower respiratory tract infection (mean age 59 ± 12 years). Following adjustment for age, ETV7, GBP1, GBP5, P2RY14 and BLK were significantly differentially expressed between patients with TB and those with LRI. A general discriminant analysis generated a three-gene signature ( BAFT2, ETV7 and CD1C ), which diagnosed TB with an area under the receiver operating characteristic curve (AUC) of 0.86 (95% CI, 0.69 - 1.00), sensitivity of 69.23% (95% CI, 38.57%-90.91%) and specificity of 94.12% (95% CI, 71.31%-99.85%)., Conclusion: The three-genes signature may have potential to improve diagnosis of TB in a hospitalised low-burden setting. However, the influence of confounding variables or covariates such as age requires further evaluation in larger studies.

The advent and evolution of next generation sequencing has considerably impacted genomic research. Until recently, South African researchers were unable to access affordable platforms capable of human whole genome sequencing locally and DNA samples had to be exported. Here we report the whole genome sequences of the first six human DNA samples sequenced and analysed at the South African Medical Research Council's Genomics Centre. We demonstrate that the data obtained is of high quality, with an average sequencing depth of 36.41, and that the output is comparable to data generated internationally on a similar platform. The Genomics Centre creates an environment where African researchers are able to access world class facilities, increasing local capacity to sequence whole genomes as well as store and analyse the data.

Type 2 diabetes (T2D) is characterized by metabolic derangements that cause a shift in substrate preference, inducing cardiac interstitial fibrosis. Interstitial fibrosis plays a key role in aggravating left ventricular diastolic dysfunction (LVDD), which has previously been associated with the asymptomatic onset of heart failure. The latter is responsible for 80% of deaths among diabetic patients and has been termed diabetic cardiomyopathy (DCM). Through in silico prediction and subsequent detection in a leptin receptor-deficient db/db mice model (db/db), we confirmed the presence of previously identified potential biomarkers to detect the early onset of DCM. Differential expression of Lysyl Oxidase Like 2 (LOXL2) and Electron Transfer Flavoprotein Beta Subunit (ETFβ), in both serum and heart tissue of 6-16-week-old db/db mice, correlated with a reduced left-ventricular diastolic dysfunction as assessed by high-resolution Doppler echocardiography. Principal component analysis of the combined biomarkers, LOXL2 and ETFβ, further displayed a significant difference between wild type and db/db mice from as early as 9 weeks of age. Knockdown in H9c2 cells, utilising siRNA of either LOXL2 or ETFβ, revealed a decrease in the expression of Collagen Type I Alpha1 (COL1A1), a marker known to contribute to enhanced myocardial fibrosis. Additionally, receiver-operating curve (ROC) analysis of the proposed diagnostic profile showed that the combination of LOXL2 and ETFβ resulted in an area under the curve (AUC) of 0.813, with a cut-off point of 0.824, thus suggesting the favorable positive predictive power of the model and further supporting the use of LOXL2 and ETFβ as possible early predictive DCM biomarkers.

Spent coffee ground (SCG) is the main residue generated during the production of instant coffee by thermal water extraction from roasted coffee beans. This waste is composed mainly of polysaccharides such as cellulose and galactomannans that are not solubilised during the extraction process, thus remaining as unextractable, insoluble solids. In this context, the application of an enzyme cocktail (mannanase, endoglucanase, exoglucanase, xylanase and pectinase) with more than one component that acts synergistically with each other is regarded as a promising strategy to solubilise/hydrolyse remaining solids, either to increase the soluble solids yield of instant coffee or for use as raw material in the production of bioethanol and food additives (mannitol). Wild fungi were isolated from both SCG and coffee beans and screened for enzyme production. The enzymes produced from the selected wild fungi and recombinant fungi were then evaluated for enzymatic hydrolysis of SCG, in comparison to commercial enzyme preparations. Out of the enzymes evaluated on SCG, the application of mannanase enzymes gave better yields than when only cellulase or xylanase was utilised for hydrolysis. The recombinant mannanase (Man1) provided the highest increments in soluble solids yield (17 %), even when compared with commercial preparations at the same protein concentration (0.5 mg/g SCG). The combination of Man1 with other enzyme activities revealed an additive effect on the hydrolysis yield, but not synergistic interaction, suggesting that the highest soluble solid yields was mainly due to the hydrolysis action of mannanase.

Consolidated bioprocessing (CBP), which integrates enzyme production, saccharification and fermentation into a one step process, is a promising strategy for the effective ethanol production from cheap lignocellulosic and starchy materials. CBP requires a highly engineered microbial strain able to both hydrolyze biomass with enzymes produced on its own and convert the resulting simple sugars into high-titer ethanol. Recently, heterologous production of cellulose and starch-degrading enzymes has been achieved in yeast hosts, which has realized direct processing of biomass to ethanol. However, essentially all efforts aimed at the efficient heterologous expression of saccharolytic enzymes in yeast have involved laboratory strains and much of this work has to be transferred to industrial yeasts that provide the fermentation capacity and robustness desired for large scale bioethanol production. Specifically, the development of an industrial CBP amylolytic yeast would allow the one-step processing of low-cost starchy substrates into ethanol. This article gives insight in the current knowledge and achievements on bioethanol production from starchy materials with industrial engineered S. cerevisiae strains.

The development of a yeast that converts raw starch to ethanol in one step (called consolidated bioprocessing) could yield large cost reductions in the bioethanol industry. The aim of this study was to develop an efficient amylolytic Saccharomyces cerevisiae strain suitable for industrial bioethanol production. A native and codon-optimized variant of the Aspergillus awamori glucoamylase gene were expressed in the S. cerevisiae Y294 laboratory strain. Codon optimization resulted to be effective and the synthetic sequence sGAI was then δ-integrated into a S. cerevisiae strain with promising industrial fermentative traits. The mitotically stable recombinant strains showed high enzymatic capabilities both on soluble and raw starch (2425 and 1140 nkat/g dry cell weight, respectively). On raw corn starch, the engineered yeasts exhibited improved fermentative performance with an ethanol yield of 0.42 (g/g), corresponding to 75 % of the theoretical maximum yield.