A data analysis dissertation of between 4000 and 6000 words (not including references, headers, or tables) on the
subject of ‘the beehive microbiome as an indicator of environmental pathogens’. The following is the description
of the project:
“Infectious diseases pose a serious threat to food security, biodiversity and human health. Although incidents
may occur naturally human actions such as farming and environment pollution are heavily implicated in the
spread of pathogenic bacteria. Therefore, holistic strategies that are able to forecast disease threats to plants,
animals and humans are urgently needed. Here we propose to use beehives as a non-invasive biological tool to
monitor the presence of environmental pathogens. Recently, our research group has discovered that honey and
beebread carry an enormous variety of bacterial species, especially those that are beneficial to honeybees. This
remarkable finding was observed following a 16S rDNA ion torrent sequencing analysis on samples that were
collected from 26 beehives in the southeast of England. We also observed that the bacterial diversity was
dependent on the type of sample collected and local plant sources, suggesting that every hive possesses their
own microbiome and that this specific fingerprint is affected by the nectar and pollen gathered from local plants.
The aim of this project will be to further analyse these preliminary data and determine whether the microbiome
of the beehives can also inform of pathogenic bacteria.”
Use the attached Excel sheet (the tab ‘OTU’s normalised data’) of data, and the attached PDF with a guide on
layout. The data should be presented in at least one graph and one table, as well as being written. The objective
of the project is to attempt to characterise the beehive microbiome with the identification of bacterial
communities associated with crop/plant pathogens. Therefore, plant/crop pathogens in the Excel spreadsheet
should be used.
– Objective should be clearly indicated in the abstract: characterisation of the beehive microbiome for the
identification of bacterial communities associated with crop/plant pathogens
Highlight the concept of apibiome, which is the microbiome of the whole beehive as a valuable indicator of the
health of the bees and their surrounding ecosystem (plants and crops)
Use data from samples (different beehives) showing the presence of plant/crop pathogens and determine whether
they share the same type of bacterial communities.
– Fluctuations of microbes that are abundant and prevalent in samples where pathogens have been detected could
be used as indicators (a warning) of pathogen incidence