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Launched in 2015, the large-scale initiative Indonesian Biodiversity Discovery and Information System (IndoBioSys) is a multidisciplinary German-Indonesian collaboration with the main goal of establishing a standardised framework for species discovery and all associated steps. One aspect of the project includes the application of DNA barcoding for species identification and biodiversity assessments. In this framework, we conducted a large-scale assessment of the insect fauna of the Mount Halimun-Salak National Park which is one of the largest tropical rain-forest ecosystems left in West Java. In this study, we present the results of processing 5,034 specimens of Phoridae (scuttle flies) via DNA barcoding. Despite limited sequencing success, we obtained more than 500 clusters using different algorithms (RESL, ASAP, SpeciesIdentifier). Moreover, Chao statistics indicated that we drastically undersampled all trap sites, implying that the true diversity of Phoridae is, in fact, much higher. With this data release, we hope to shed some light on the hidden diversity of this megadiverse group of flies.

Arthropods account for a large proportion of animal biomass and diversity in terrestrial systems, making them crucial organisms in our environments. However, still too little is known about the highly abundant and megadiverse groups that often make up the bulk of collected samples, especially in the tropics. With molecular identification techniques ever more evolving, analysis of arthropod communities has accelerated. In our study, which was conducted within the Global Malaise trap Program (GMP) framework, we operated two closely placed Malaise traps in Padang, Sumatra, for three months. We analyzed the samples by DNA barcoding and sequenced a total of more than 70,000 insect specimens. For sequence clustering, we applied three different delimitation techniques, namely RESL, ASAP, and SpeciesIdentifier, which gave similar results. Despite our (very) limited sampling in time and space, our efforts recovered more than 10,000 BINs, of which the majority are associated with "dark taxa". Further analysis indicates a drastic undersampling of both sampling sites, meaning that the true arthropod diversity at our sampling sites is even higher. Regardless of the close proximity of both Malaise traps (< 360 m), we discovered significantly distinct communities.

We present the first regional inventory of the fauna of Chalcididae in the Peruvian Amazon, with a nearly 6-fold increase in the number of species recorded for the country. A total of 418 specimens of Chalcididae were collected between 2000 and 2017 at the Panguana Reserve, Peruvian Amazon, 400 of which were obtained using Malaise traps and the remaining 18 specimens by canopy fogging. The morphological analyses indicated that these specimens represent 183 species of Chalcididae in 10 different genera, with 173 new to Peru and 134 potentially new species. We submitted 268 specimens, representing 167 species, to DNA barcoding. Of these, 141 specimens yielded sequences, 136 of them with a minimum of 300 bp. Sixty specimens were assigned a BIN by the Barcode of Life Database System (BOLD), resulting in 50 BINs. A cluster analysis of 138 individuals that yielded DNA sequences longer than 100 bp revealed 118 MOTUs (molecular operative taxonomic units), all of them highly congruent with the morphological data. Prior to the present study, 37 species in 9 genera of Chalcididae were known from Peru. With our results, this number was increased to 210 species in 13 genera. The present study is the result of a joint effort between the SNSB - Zoologische Staatssammlung München, Germany (ZSM) and the Insect Biodiversity Laboratory of the Universidade Federal do Espírito Santo, Vitória, Brazil (LaBI-UFES), intending to apply an accelerated taxonomic treatment of the Chalcididae of the Panguana reserve using traditional morphological approaches in combination with DNA barcoding. The complete molecular dataset and associated voucher information is publicly available through BOLD. The new species that were discovered as part of the study are being formally described elsewhere as part of taxonomic treatments of Neotropical and world generic revisions at LaBI-UFES.

We present the results of a DNA barcoding pipeline that was established as part of the German-Indonesian IndobioSys project - Indonesian Biodiversity Information System. Our data release provides the first large-scale diversity assessment of Indonesian coleoptera obtained by canopy fogging. The project combined extensive fieldwork with databasing, DNA barcode based species delineation and the release of results in collaboration with Indonesian counterparts, aimed at supporting further analyses of the data. Canopy fogging on 28 trees was undertaken at two different sites, Cikaniki and Gunung Botol, in the south-eastern area of the Gunung Halimun-Salak National Park in West Java, Indonesia. In total, 7,447 specimens of Coleoptera were processed, of which 3,836 specimens produced DNA barcode sequences that were longer than 300 bp. A total of 3,750 specimens were assigned a Barcode Index Number (BIN), including 2,013 specimens from Cikaniki and 1,737 specimens from Gunung Botol. The 747 BINs, that were obtained, represented 39 families of Coleoptera. The distribution of specimens with BINs per tree was quite heterogeneous in both sites even in terms of the abundance of specimens or diversity of BINs. The specimen distribution per taxon was heterogeneous as well. Some 416 specimens could not be identified to family level, corresponding to 72 BINs that lack a family level identification. The data have shown a large heterogeneity in terms of abundance and distribution of BINs between sites, trees and families of Coleoptera. From the total of 747 BINs that were recovered, 421 (56%) are exclusive from a single tree. Although the two study sites were in close proximity and separated by a distance of only about five kilometres, the number of shared BINs between sites is low, with 81 of the 747 BINs. With this data release, we expect to shed some light on the largely hidden diversity in the canopy of tropical forests in Indonesia and elsewhere.

The Indonesian archipelago features an extraordinarily rich biota. However, the actual taxonomic inventory of the archipelago remains highly incomplete and there is hardly any significant taxonomic activity that utilises recent technological advances. The IndoBioSys project was established as a biodiversity information system aiming at, amongst other goals, creating inventories of the Indonesian entomofauna using DNA barcoding. Here, we release the first large scale assessment of the megadiverse insect groups that occur in the Mount Halimun-Salak National Park, one of the largest tropical rain-forest ecosystem in West Java, with a focus on Hymenoptera, Coleoptera, Diptera and Lepidoptera collected with Malaise traps. From September 2015 until April 2016, 34 Malaise traps were placed in different localities in the south-eastern part of the Halimun-Salak National Park. A total of 4,531 specimens were processed for DNA barcoding and in total, 2,382 individuals produced barcode compliant records, representing 1,195 exclusive BINs or putative species in 98 insect families. A total of 1,149 BINs were new to BOLD. Of 1,195 BINs detected, 804 BINs were singletons and more than 90% of the BINs incorporated less than five specimens. The astonishing heterogeneity of BINs, as high as 1.1 exclusive BIN per specimen of Diptera successfully processed, shows that the cost/benefit relationship of the discovery of new species in those areas is very low. In four genera of Chalcidoidea, a superfamily of the Hymenoptera, the number of discovered species was higher than the number of species known from Indonesia, suggesting that our samples contain many species that are new to science. Those numbers shows how fast molecular pipelines contribute substantially to the objective inventorying of the fauna giving us a good picture of how potentially diverse tropical areas might be.

Here we present a general collecting and preparation protocol for DNA barcoding of Lepidoptera as part of large-scale rapid biodiversity assessment projects, and a comparison with alternative preserving and vouchering methods. About 98% of the sequenced specimens processed using the present collecting and preparation protocol yielded sequences with more than 500 base pairs. The study is based on the first outcomes of the Indonesian Biodiversity Discovery and Information System (IndoBioSys). IndoBioSys is a German-Indonesian research project that is conducted by the Museum für Naturkunde in Berlin and the Zoologische Staatssammlung München, in close cooperation with the Research Center for Biology – Indonesian Institute of Sciences (RCB-LIPI, Bogor).

The German Barcoding initiatives BFB and GBOL have generated a reference library of more than 16,000 metazoan species, which is now ready for applications concerning next generation molecular biodiversity assessments. To streamline the barcoding process, we have developed a meta-barcoding pipeline: We pre-sorted a single malaise trap sample (obtained during one week in August 2014, southern Germany) into 12 arthropod orders and extracted DNA from pooled individuals of each order separately, in order to facilitate DNA extraction and avoid time consuming single specimen selection. Aliquots of each ordinal-level DNA extract were combined to roughly simulate a DNA extract from a non-sorted malaise sample. Each DNA extract was amplified using four primer sets targeting the CO1-5' fragment. The resulting PCR products (150-400bp) were sequenced separately on an Illumina Mi-SEQ platform, resulting in 1.5 million sequences and 5,500 clusters (coverage ≥10; CD-HIT-EST, 98%). Using a total of 120,000 DNA barcodes of identified, Central European Hymenoptera, Coleoptera, Diptera, and Lepidoptera downloaded from BOLD we established a reference sequence database for a local CUSTOM BLAST. This allowed us to identify 529 Barcode Index Numbers (BINs) from our sequence clusters derived from pooled Malaise trap samples. We introduce a scoring matrix based on the sequence match percentages of each amplicon in order to gain plausibility for each detected BIN, leading to 390 high score BINs in the sorted samples; whereas 268 of these high score BINs (69%) could be identified in the combined sample. The results indicate that a time consuming presorting process will yield approximately 30% more high score BINs compared to the non-sorted sample in our case. These promising results indicate that a fast, efficient and reliable analysis of next generation data from malaise trap samples can be achieved using this pipeline.

Since December 2019, a new form of Severe Acute Respiratory Syndrome (SARS) has emerged worldwide, caused by SARS coronavirus 2 (SARS-CoV-2). This disease was called COVID-19 and was declared a pandemic by the World Health Organization in March 2020. Symptoms can vary from a common cold to severe pneumonia, hypoxemia, respiratory distress, and death. During this period of world stress, the medical and scientific community were able to acquire information and generate scientific data at unprecedented speed, to better understand the disease and facilitate vaccines and therapeutics development. Notably, bioinformatics tools were instrumental in decoding the viral genome and identifying critical targets for COVID-19 diagnosis and therapeutics. Through the integration of omics data, bioinformatics has also improved our understanding of disease pathogenesis and virus-host interactions, facilitating the development of targeted treatments and vaccines. Furthermore, molecular biology techniques have accelerated the design of sensitive diagnostic tests and the characterization of immune responses, paving the way for precision medicine approaches in treating COVID-19. Our analysis highlights the indispensable contributions of bioinformatics and molecular biology to the global effort against COVID-19. In this review, we aim to revise the COVID-19 features, diagnostic, prevention, treatment options, and how molecular biology, modern bioinformatic tools, and collaborations have helped combat this pandemic. An integrative literature review was performed, searching articles on several sites, including PUBMED and Google Scholar indexed in referenced databases, prioritizing articles from the last 3 years. The lessons learned from this COVID-19 pandemic will place the world in a much better position to respond to future pandemics.