Correlation between Pest Abundance and Prevalence of Honeybee Pathogens at Selected Apiaries in Kenya, 2013/2014

Routine screening for pathogens plays an invaluable role in the detection of diseases in pre-clinical stages and prevention of losses. The present study was part of a larger surveillance effort to identify the determinants of African honeybee health, and particularly, to quantify honeybee pest abundance and to determine the prevalence of pathogens across Kenya, where 161 colonies from 32 apiaries were examined. From each colony, 20 individuals of foragers, nurse bees, worker pupae and drone pupae were sampled separately. These were organized as 30 foragers, 32 nurse bees, 28 worker pupae and 10 drone pupae pools. The pest abundance was determined by counting the number per colony and their occurrence in each apiary was computed by calculating the arithmetic mean values. Honeybee diseases were detected by PCR and the prevalence per apiary was computed. Varroa destructor mites and Aethina tumida were the most abundant pests. There was near universal presence of Varroa and to a smaller extent A. tumida in majority of the locations visited. Overall, Varroa destructor virus 1, deformed wing virus and black queen cell virus were detected with the highest prevalence in the apiaries at 66%, 69% and 69% respectively. Other pathogens detected were Sacbrood virus, Israeli acute paralysis virus, Acute bee paralysis virus and Nosema ceranae at 28%, 22%, 19% and 13% respectively. Spearman Ranked Correlation between the mean pest count and the specific pathogen prevalence revealed an overall positive though non-significant correlation between the pests and most pathogens. The exceptional finding of this study was the identification of a key association between the abundance of A. tumida and Nosema infection, with a statistically significant positive correlation (R = 0.89803; P = 0.01507). Further studies will be required to understand the nature of this association with the aim of unravelling if the A. tumida has a biological role in Nosema transmission. Keywords: Aethina tumida, Nosema, DWV, VDV 1, BQC

Demineralization enables reeling of wild Silkmoth cocoons

Wild Silkmoth cocoons are difficult or impossible to reel under conditions that work well for cocoons of the Mulberry silkmoth, Bombyx mori. Here we report evidence that this is caused by mineral reinforcement of Wild Silkmoth cocoons and that washing these minerals out allows for the reeling of commercial lengths of good quality fibers with implications for the development of the “Wild Silk” industry. We show that in the Lasiocampid silkmoth Gonometa postica, the mineral is whewellite (calcium oxalate monohydrate). Evidence is presented that its selective removal by ethylenediaminetetraacetic acid (EDTA) leaves the gum substantially intact, preventing collapse and entanglement of the network of fibroin brins, enabling wet reeling. Therefore, this method clearly differs from the standard “degumming” and should be referred to as “demineralizing”. Mechanical testing shows that such preparation results in reeled silks with markedly improved breaking load and extension to break by avoiding the damage produced by the rather harsh degumming, carding, or dry reeling methods currently in use, what may be important for the development of the silk industries not only in Asia but also in Africa and South America

Analysis of Honey Bee Hive Products as a Model for Monitoring Pesticide Usage in Agroecosystems

Global food and nutritional security majorly rely on honey bees for pollination. Furthermore, honey bees (Apis mellifera), are considered as reliable biological indicators of environmental contamination because they pick up chemical pollutants in the air or in flowers as they search for food. As a result, the honey bee colony environment acts as a reservoir for a diversity of resources of floral origin and therefore analyzing hive products is more cost effective compared to monitoring individual crops. Effective methods for monitoring agrochemicals contamination in the environment can therefore be achieved by continuous analysis of honey bee products. We investigated pesticide residues in honey and pollen collected from honey bee hives in various agro-ecological zones across Kenya over a period of two years (September 2013 to August 2015) to determine the circulating organic chemical pollutants in the environment. A total of 36 pesticide residues were detected belonging to three chemical classes; insecticides (>50%) fungicides (27%) and herbicides (20%) with majority of the pesticides detected in pollen compared to honey. Although herbicides appeared to be the least prevalent, they were detected at the highest concentrations of up to 356 ppb in honey compared to insecticides which were detected at fairly low concentrations (0.1 to 53 ppb). Our findings highlight the need to create greater awareness of the ecological consequences of wide scale use of agro-chemicals in agriculture.  Keywords: Pesticide residues, honey bees (Apis mellifera), honey and polle

Identification of stingless bees (Hymenoptera: Apidae) in Kenya using Morphometrics and DNA barcoding

Stingless bees are important pollinators of wild plants and crops. The identity of stingless bee species in Africa has not been fully documented. The present study explored the utility of morphometrics and DNA barcoding for identification of African stingless bee populations, and to further employ these tools to identify potential cryptic variation within species. Stingless bee samples were collected from three ecological zones, namely Kakamega Forest, Mwingi and Arabuko-Sokoke Forest, which are geographically distant and cover high, medium and low altitudes, respectively. Forewing and hind leg morphometric characters were measured to determine the extent of morphological variation between the populations. DNA barcodes were generated from the mitochondrial cytochrome c-oxidase I (COI) gene. Principal Component Analysis (PCA) on the morphometric measurements separated the bee samples into three clusters: (1) Meliponula bocandei; (2) Meliponula lendliana + Plebeina hildebrandti; (3) Dactylurina schmidti + Meliponula ferruginea black + Meliponula ferruginea reddish brown, but Canonical Variate Analysis (CVA) separated all the species except the two morphospecies (M. ferruginea reddish brown and black). The analysis of the COI sequences showed that DNA barcoding can be used to identify all the species studied and revealed remarkable genetic distance (7.3%) between the two M. ferruginea morphs. This is the first genetic evidence that M. ferruginea black and M. ferruginea reddish brown are separate species

Compounds extracted from heads of African stingless bees (Hypotrigona species) as a prospective taxonomic tool

Stingless bees are important pollinators of plants, and also producers of honey. Species within the African stingless bee genus Hypotrigona are difficult to differentiate due to morphological similarities. Chemical profiles of whole head extracts from workers of three Hypotrigona species: H. gribodoi, H. araujoi and H. ruspolii were studied by gas chromatography–mass spectrometry. A total of 50 components belonging to six chemical classes: hydrocarbons, aldehydes, alcohols, terpenoids, steroids and fatty acids were identified. Twenty-nine compounds were found in H. araujoi, 26 in H. gribodoi and 33 in H. ruspolii head extracts. Hydrocarbons, alcohols and fatty acids were the major classes, whilst steroids and terpenoids were minor. Aldehydes were found only in H. ruspolii while terpenoids were only present in extracts of H. gribodoi and H. araujoi. Eight chemical compounds were specific to H. araujoi, six to H. gribodoi and nine to H. ruspolii, showing both qualitative and quantitative differences. Workers were successfully grouped into their respective species using their chemical profiles. This study shows that head extracts can be used as a reliable taxonomic tool for identifying and differentiating Hypotrigona species.The European Union (EU) (Grant Contract No. DCI-FOOD/2013/313-659: African Reference Laboratory (with satellite stations) for the Management of Pollination Bee Diseases and Pests for Food Security); the South African National Research Foundation (NRF) Research Career Advancement Fellowship (Grant no: 91419) to AAY; NRF Incentive Funding for Rated Researchers to CWWP and AAY; UK Aid from the UK Government; Swedish International Development Cooperation Agency (Sida); the Swiss Agency for Development and Cooperation (SDC) and the Kenyan Government. The first author was supported by a German Academic Exchange Service (DAAD) In-Region Postgraduate Scholarship.https://link.springer.com/journal/492019-04-01hj2018Zoology and Entomolog

The Utility of AISA Eagle Hyperspectral Data and Random Forest Classifier for Flower Mapping

Peer reviewe

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN