Human filarial infections are vector-borne nematode infections, which include lymphatic filariasis, onchocerciasis, loiasis, and mansonella filariasis. With a high prevalence in developing countries, filarial infections are responsible for some of the most debilitating morbidities and a vicious cycle of poverty and disease. Global initiatives set to eradicate these infections include community mass treatments, vector control, provision of care for morbidity, and search for vaccines. However, there are growing challenges associated with mass treatments, vector control, and antifilarial vaccine development. With the emergence of genome editing tools and successful applications in other infectious diseases, the integration of genetic editing techniques in future control strategies for filarial infections would offer the best option for eliminating filarial infections. In this review, we briefly discuss the mechanisms of the three main genetic editing techniques and explore the potential applications of these powerful tools to control filarial infections.

Background: Lymphatic Filariasis (LF), a neglected tropical disease, has been speculated to be complicated by secondary bacteria, yet a systematic documentation of these bacterial populations is lacking. Thus, the primary focus of this study was to profile bacteria diversity in the progression of filarial lymphedema among LF individuals with or without wounds.Methods: A cross‐sectional study design recruited 132 LF individuals presenting with lymphedema with or without wounds from eight communities in the Ahanta West District in the Western Region, Ghana. Swabs from the lymphedematous limbs, ulcers, pus, and cutaneous surfaces were cultured using standard culture‐based techniques. The culture isolates were subsequently profiled using Matrix‐assisted Laser Desorption/Ionization Time of Flight Mass Spectrometry.Results: Of the 132 LF participants recruited, 65% (85) had filarial lymphedema with no wounds. In total, 84% (235) of the bacterial isolates were identified. The remaining 16% (46) could not be identified with the method employed. Additionally, 129(55%) of the strains belonged to the phylum Firmicutes, while 61 (26%) and 45 (19%) represented Proteobacteria and Actinobacteria, respectively. Generally, irrespective of the samples type (i.e., wound sample and non‐wound samples), there was a sharp increase of bacteria diversity from Stages 1 to 3 and a drastic decrease in these numbers by Stage 4, followed by another surge and a gradual decline in the advanced stages of the disease. The Shannon Diversity Index and Equitability for participants with and without wounds were (3.482, 0.94) and (3.023, 0.75), respectively. Further, Staphylococcus haemolyticus and Escherichia coli showed resistance to tetracycline, chloramphenicol, and penicillin.Conclusion: The present study reveals a sharp decline in bacterial load at the late stages of filarial lymphedema patients. In addition, we report an emerging antimicrobial resistance trend of S. haemolyticus and E. coli against commonly used antibiotics such as tetracycline, chloramphenicol, and penicillin in communities endemic for LF in the Ahanta West District, Ghana. This could pose a huge challenge to the management of the disease; particularly as current treatments are not quite effective against the infection.

Single nucleotide polymorphisms (SNP) are associated with diseases and drug response variabilities in humans. Elucidating the damaging and disease-associated SNPs using wet-laboratory approaches can be challenging and resource-demanding due to the large number of SNPs in the human genome. Due to the growth in the field of computational biology and bioinformatics, algorithms have been developed to help screen and filter out the most deleterious SNPs that are worth considering for wet-laboratory studies. Here we review the existing in-silico based methods used to predict and characterize the effects of SNPs on protein structure and function. This cutting-edge approach will facilitate the search for novel therapeutics, help understand the etiology of diseases and fast-track the personalized medicine agenda.

Human gremlin-1 is a physiologically versatile signaling molecule that has been associated with several human diseases including cancer. The ability of gremlin-1 to induce fibrosis in organs and transduce angiogenesis makes it a target for cancer therapy. RNAi-based therapy has proven to be very efficient and specific in tumor growth inhibition. The efficacy and specificity of siRNA-mediated gene silencing depends on the designing approaches. Here, empirical guidelines for siRNA design and comprehensive target site availability analysis were used to select effective siRNA from a plethora of potential candidates designed using several computation algorithms. Then, the selected siRNA candidates were subjected to stringent similarity searches in order to obtain siRNA candidates with reduced off-target effects (high specificity). The best candidates were compared to experimentally successful gremlin-1 siRNAs in order to predict the silencing potency of the selected siRNAs. siRNA-6 (sense strand: 5’-CCAAGAAAUUCACUACCAU-3’), siRNA-7 (sense strand: 5’-CCAUGAUGGUCACACUCAA-3’) and siRNA-47 (sense strand: 5’-GGCCCAGCACAAUGACUCA-3’) were predicted to be highly effective siRNA candidates for gremlin-1 silencing. These siRNAs can be considered for RNAi-based therapy because off-target effects are predicted to be minimal.