Illegal wildlife trade (IWT) is considered one of the largest global illegal industries that negatively impacts biodiversity and sustainable development worldwide. DNA barcoding coupled with high-throughput sequencing has been shown to be useful in identifying taxa affected by IWT and has been routinely used during the last decades. However, for countries lacking laboratory infrastructures and sequencing units or trained staff, the application of DNA barcoding tools in conservation actions and policies is limited and dependent on slow sample export processes and molecular analyses carried out abroad. Guinea-Bissau (GB) is located on the West-African coast and has one of the lowest human development indices worldwide, while being a biodiversity hotspot facing many conservation challenges due to illegal commercial hunting and trade in bushmeat and live individuals. Here, we explore the potential of using inexpensive and portable miniaturised laboratory equipment (MLE) to i) identify species illegally traded in GB using DNA barcoding methods and ii) improve molecular biology and conservation genetic education and training in GB. Our overarching aim is to raise awareness of the current gap between the need to apply conservation genetic technologies in GB and the inability to do so due to a lack of laboratory infrastructures, sequencing units and opportunities for molecular biology training. We show that MLE can be a solution to accelerate the use of DNA barcoding methods to understand IWT and to train students, technicians and staff from governmental agencies dedicated to investigating environmental crimes, ultimately advancing the discipline of conservation genetics in the country.

This study used 33 tissue samples collected as part of other studies that investigated wild meat hunting, trade and consumption in several locations in Guinea-Bissau (Minhós et al. 2013; Ferreira da Silva et al. 2021).

DNA was extracted using ThermoFisher’s MagMAX DNA Multi-Sample Ultra 2.0 Kit on the ThermoFisher Kingfisher Apex DNA extraction platform using default parameters. For the PCR amplification we used (1) primers designed by Gaubert et al. (2015) for the identification of bushmeat samples that amplify the first 402 bp of cytochrome b (cyt b) and a 390 bp of the 12S region, and (2) approximately 250 bp of the 16S rRNA gene using primers from Vences et al. (2016) that were designed to amplify vertebrate DNA from environmental DNA samples. Fragments were amplified by PCR in 30ul total volume reaction, using 15 ul of Qiagen Multiplex PCR Mix (Qiagen, GER), 0.6 uM of forward and reverse primers and 1ul of DNA. Thermal cycling was performed in a T100 Thermal Cycler (BioRad). Cycling conditions consisted of 94°C for 3 min, followed by 35 cycles at 92 °C for 30’’, the primers specific annealing temperature for 30 s (CytB – 48°C, 12S – 56°C and 16S – 59°C) and 72°C for 30 s, followed by a final extension of 72°C for 15 min. A template-free PCR was included in each amplification to control for potential contamination. Amplification success was checked on 2% agarose gels.

The sequencing was carried out on the ONT’s MinION Mk1C platform using the native barcoding kit (ONT, SQK-NBD114.96) according to the manufacturer’s manual with minimal exceptions. In brief, the ends of the DNA amplicons were first prepared for index ligation using the NEBNext Ultra II End Repair / dA-tailing module (NEB, USA), here we extended the reaction time to 30 min at 20C and 30 min at 65C, then individual indices were aligned using the NEB Blunt/TA Ligase Master Mix (NEB, USA), cleaned with AMPure XP Beads (Beckman Coulter, USA) and then pooled in equal ratios. Sequencing adapters were ligated to the indices using the NEBNext Quick Ligation Module (NEB, USA) and the reaction cleaned using AMPureXP Beads (Beckman Coulter, USA) with ONT’s Short Fragment Buffer (SFB). The final library was quantified using the Qubit 4 Fluorometer and about 200ng loaded onto an ONT Flongle sequencing flowcell.

We followed the bioinformatic pipeline described in Pomerantz et al. 2022. First the raw pod5 files were converted to the fastq format and demultiplexed using Dorado 0.5.0 (https://github.com/nanoporetech/dorado). Next, the number of reads and their quality were assessed using NanoPlot (https://github.com/wdecoster/NanoPlot) and we only retained reads with a Phred score of at least 17 with NanoFilt (https://github.com/wdecoster/nanofilt). Priming sites were removed from the reads using cutadapt (https://github.com/marcelm/cutadapt/; Martin 2011) and the consensus sequences reconstructed using NGSpeciesID (Sahlin et al. 2021). We carried out consensus polishing within NGSpeciesID using ONT’s Medaka software (https://github.com/nanoporetech/medaka). To identify the sample to the species level, we compared the sequences to available data on NCBI (http://www.ncbi.nlm.nih.gov/) using Nucleotide BLAST (Boratyn et al. 2013).

References

Minhós T, Nixon E, Sousa C, Vicente LM, da Silva MF, Sá R, Bruford MW (2013a) Genetic evidence for spatio-temporal changes in the dispersal patterns of two sympatric African colobine monkeys. Am J Phys Anthropol, 150, 464-474.

Ferreira da Silva MJ, Camará M, Egeter B, Minhós T, Bruford MW, Godinho R (2021a) Using meta-barcoding tools to monitor primate meat consumption at dedicated establishments in Guinea-Bissau, West Africa. In: Collection: Trends in Biodiversity and Evolution | TiBE2020 – Metabarcoding and Metagenomics p. e65575. ARPHA Conference Abstracts, Vairão, Portugal.

Gaubert P, Njiokou F, Olayemi A, Pagani P, Dufour S, Danquah E, Nutsuakor MEK, Ngua G, Missoup A-D, Tedesco PA, Dernat R, Antunes A (2015) Bushmeat genetics: setting up a reference framework for the DNA typing of African forest bushmeat. Molecular Ecology Resources, 15, 633-651.

Vences M, Lyra ML, Perl RGB, Bletz MC, Stanković D, Lopes CM, Jarek M, Bhuju S, Geffers R, Haddad CFB, Steinfartz S (2016) Freshwater vertebrate metabarcoding on Illumina platforms using double-indexed primers of the mitochondrial 16S rRNA gene. Conservation Genetics Resources, 8, 323-327.

Pomerantz A, Sahlin K, Vasiljevic N, Seah A, Lim M, Humble E, Kennedy S, Krehenwinkel H, Winter S, Ogden R, Prost S (2022) Rapid in situ identification of biological specimens via DNA amplicon sequencing using miniaturized laboratory equipment. Nature Protocols, 17, 1415-1443.

Martin M (2011) Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet journal, 17, 10-12.

Sahlin K, Lim MCW, Prost S (2021) NGSpeciesID: DNA barcode and amplicon consensus generation from long-read sequencing data. Ecology and Evolution, 11, 1392-1398.

Boratyn GM, Camacho C, Cooper PS, Coulouris G, Fong A, Ma N, Madden TL, Matten WT, McGinnis SD, Merezhuk Y, Raytselis Y, Sayers EW, Tao T, Ye J, Zaretskaya I (2013) BLAST: a more efficient report with usability improvements. Nucleic Acids Res, 41, W29-33.