Machine learning approach to support taxonomic species discrimination based on helminth collections data.

BACKGROUND: There are more than 300 species of capillariids that parasitize various vertebrate groups worldwide. Species identification is hindered because of the few taxonomically informative structures available, making the task laborious and genus definition controversial. Thus, its taxonomy is one of the most complex among Nematoda. Eggs are the parasitic structures most viewed in coprological analysis in both modern and ancient samples; consequently, their presence is indicative of positive diagnosis for infection. The structure of the egg could play a role in genera or species discrimination. Institutional biological collections are taxonomic repositories of specimens described and strictly identified by systematics specialists. METHODS: The present work aims to characterize eggs of capillariid species deposited in institutional helminth collections and to process the morphological, morphometric and ecological data using machine learning (ML) as a new approach for taxonomic identification. Specimens of 28 species and 8 genera deposited at Coleção Helmintológica do Instituto Oswaldo Cruz (CHIOC, IOC/FIOCRUZ/Brazil) and Collection de Nématodes Zooparasites du Muséum National d'Histoire Naturelle de Paris (MNHN/France) were examined under light microscopy. In the morphological and morphometric analyses (MM), the total length and width of eggs as well as plugs and shell thickness were considered. In addition, eggshell ornamentations and ecological parameters of the geographical location (GL) and host (H) were included. RESULTS: The performance of the logistic model tree (LMT) algorithm showed the highest values in all metrics compared with the other algorithms. Algorithm J48 produced the most reliable decision tree for species identification alongside REPTree. The Majority Voting algorithm showed high metric values, but the combined classifiers did not attenuate the errors revealed in each algorithm alone. The statistical evaluation of the dataset indicated a significant difference between trees, with GL + H + MM and MM only with the best scores. CONCLUSIONS: The present research proposed a novel procedure for taxonomic species identification, integrating data from centenary biological collections and the logic of artificial intelligence techniques. This study will support future research on taxonomic identification and diagnosis of both modern and archaeological capillariids.

African helminth infection out of Africa: Paleoparasitological and paleogenetic investigations in Pretos Novos cemetery, Rio de Janeiro, Brazil (1769-1830).

Pretos Novos cemetery (PNC), Rio de Janeiro, Brazil (1769-1830) was created exclusively to bury enslaved Africans who died upon arrival at the city or before being sold in the slave market. The PNC site may be unique in the Americas in allowing the study of African parasite infections acquired in Africa. We aimed to identify parasites infecting PNC individuals through paleoparasitological and paleogenetic analyses. The bodies had been dismembered, placed in mass graves, and burned, and most human remains collected from the site are highly fragmented and show extensive degradation. Sacrum and pelvic sediments were collected from five individuals along with seven samples of sediment from other areas of the body, as controls. Samples were submitted to three parasitological techniques and, in paleogenetic analysis, to four molecular targets. Larvae, mites, pollen grains, and structure suggestive of plants and fungus were observed, but we found no evidence of helminth infection. Ascaris sp. cytb sequence was recovered in one individual. We emphasize that, even with the extensive degradation of PNC human remains and the process of curation of samples, it was possible to recover helminth aDNA. The origin of PNC individuals confirms that these infections were brought to Brazil from western and central Africa during the colonial era.

Worldwide paleodistribution of capillariid parasites: Paleoparasitology, current status of phylogeny and taxonomic perspectives.

INTRODUCTION: Paleoparasitology, the study of parasites in the past, brings the knowledge of where and when they occurred in preterit populations. Some groups of parasites, as capillariids, have a complex and controversial systematic, hindering the paleoparasitological diagnosis. In this article, we synthesized the occurrence of capillariids in both the New and the Old World in ancient times, and discussed the difficulty of the diagnosis of species and the strategies for identification. The present review also shows the current status of the phylogeny in capillariids and indicates the necessity to try new approaches for a better understanding of capillariid paleodistribution. METHODS: For the systematic review, a predefined guideline defined by PRISMA was used. The articles collected were identified, screened, and included in the review following criteria for eligibility. The current status of the phylogeny of capillariids was accessed using MUSCLE, Bioedit v.7.0.5 and MEGA v. 7.0.21 programs. RESULTS: The review discussed 38 articles that presented information about capillariids in past populations. Most of capillariid eggs found in the New and Old World were not identified. However, Calodium hepaticum eggs were the most identified, as some from Eucoleus genus. It was observed that sites from the New World had a better chance for capillariid egg identification, due to previous knowledge of its host, when compared to the Old World. In the 18S rDNA phylogenetic analyses, two datasets were constructed, one including sequences from 7 Moravec's genera, where 3 genus-specific clusters, with high bootstrap values, could be observed for Capillaria (ML = 99%, NJ = 96%), Eucoleus (ML / NJ = 100%) and Paratrichosoma (ML / NJ = 100%). A fourth cluster of 18S rDNA dataset I revealed lack of definition of Pearsonema and Aonchotheca genera. The 18S rDNA dataset II comprised 8 Moravec's genera and defined 3 clusters, 2 genus-specific for Eucoleus (ML = 99%, NJ = 100%) and Capillaria (ML / NJ = 98%). The third 18S rDNA dataset II cluster included 6 genera and exhibited, once again, Pearsonema and Aonchotheca poor discrimination. The cox1 gene data consist of 4 Moravec's genera, and in spite of grouping some species-specific clusters, did not show genera-specific definition. CONCLUSIONS: Despite the numerous archaeological findings, both in the New and the Old Worlds, the identification of capillariid species based on the morphology and morphometry of eggs remains imprecise, often resulting in a generic diagnosis of a group or morphotype of capillariid. Capillariid is one of the most diverse group of helminths recovered in archaeological sites. The phylogenetic trees produced in this study showed limited genetic information available, unresolved genera and incongruence with the classical taxonomy. The elucidation of the paleodistribution of capillariids can give insights of the ancient host-parasite associations but also in modern sceneries.