{"paper_id":"12ed869d-3d4b-42b0-9e25-526ab031c30b","body_text":"1\n1 A Ribosomal Marker-Based Metataxonomic Framework \n2 for Environmental Surveillance of Nematodes of Public \n3 Health Importance\n4\n5 Juan P. Zuluaga1, Katherine Bedoya-Urrego2, Juan F. Alzate 2,3,*\n6\n7 1Escuela de Microbiología, Universidad de Antioquia,  Medellín, Colombia.  \n8 2Centro de Secuenciación Genómica (CNSG), Sede de Investigación Universitaria (SIU), \n9 Universidad de Antioquia, Medellín, Colombia. \n10 3Departamento de Microbiología y Parasitología, Facultad de Medicina, Universidad de \n11 Antioquia, Medellín, Colombia. \n12\n13 *Corresponding author: \n14 jfernando.alzate@udea.edu.co \n15\n16\n17\n18\n19\n20\n21\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint \n\n2\n22 ABSTRACT\n23 Metataxonomic analysis targeting the V4 region of the 18S rDNA gene, combined with \n24 molecular phylogenetic inference, was applied to detect nematode DNA of public health \n25 relevance in environmental matrices. A total of 25 mOTUs corresponding to six nematode taxa \n26 were detected in environmental samples from the Andean region of Colombia. Analysis of 12 \n27 water and sludge samples from wastewater treatment plants, 5 artisanal agricultural bioinputs, \n28 and 3 food samples revealed multiple species of public health significance: Trichuris trichiura, \n29 Enterobius vermicularis, Ascaris spp., and Necator americanus. We also confirmed zoonotic \n30 species, including Angiostrongylus cantonensis and Trichinella spp. These findings \n31 demonstrate that combining metataxonomics with molecular phylogeny provides a scalable \n32 molecular framework for the environmental surveillance of parasitic nematodes, overcoming \n33 the limitations of traditional morphological identification methods . This approach offers a \n34 replicable model for strengthening control and monitoring programs for parasitism in human \n35 populations.\n36 KEYWORDS Nematodes; Metataxonomics; Phylogenetics; Sludge; Wastewater; \n37 Bioinputs; Food\n38 INTRODUCTION\n39 Nematodes are ubiquitous metazoans found in terrestrial and aquatic habitats, \n40 parasitizing plants and animals including humans [1,2].  Approximately 30,000 species have \n41 been described, though total diversity may approach one million [3–5]. They exhibit remarkable \n42 trophic diversity, feeding on bacteria, fungi, algae, protozoa, and other nematodes, or living as \n43 facultative or obligate parasites [5,6]. In Colombia, nematode infections pose a significant public \n44 health problem, particularly among children [7], compounded by emerging anthelmintic \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint \n\n3\n45 resistance in both animal and human nematodes [8,9]. Intensive antiparasitic drug use has been \n46 selected for resistant organisms, compromising control programs [10], necessitating more \n47 sensitive molecular identification approaches.\n48 Nematode species identification typically relies on morphological characteristics of \n49 adults, larvae, and eggs [11,12]. However, classical methods often produce nonspecific \n50 identifications, underestimating parasite circulation [6,12,13]. For instance, adult and larvae \n51 morphological similarities in mouthpart, esophagus and tail structures can obscure distinctions \n52 between species, and variations in body length may not adequately reflect species differences \n53 due to overlapping size ranges. Taxonomic resolution is frequently limited to genus level; for \n54 example, hookworm egg observation cannot differentiate Necator americanus from \n55 Ancylostoma duodenale [14]. Despite their ecological and physiological diversity, nematodes \n56 conserved morphology and small size provide few phylogenetically informative characters, \n57 many showing convergent evolution [6]. In environmental samples, clinically relevant \n58 nematode eggs may be misidentified as Acari (mite) eggs due to morphological similarities, \n59 potentially leading to diagnostic errors  [15].\n60 Conventional diagnostic methods cannot adequately detect parasitic nematode diversity \n61 [6]. In previous studies, metataxonomic approaches targeting ribosomal rDNA regions have \n62 demonstrated high sensitivity and specificity for cryptic or closely related species [16–18]. \n63 Though taxonomic resolution may be limited to genus level, metataxonomics offers \n64 reproducibility, scalability, automation, and cost-effectiveness [17], and facilitates parasite \n65 detection in complex environmental matrices [18]. While widely applied in prokaryotes [19–21], \n66 nematode metataxonomic studies remain emerging [3,22].\n67 Accurate detection of parasitic nematodes in environmental matrices is critical for \n68 environmental surveillance and public health monitoring, yet remains constrained by limitations \n69 in sensitivity and taxonomic resolution. To address these challenges, this study implements \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint \n\n4\n70 metataxonomics coupled with phylogenetic analyses to detect nematodes of public health \n71 importance in environmental samples from the Andean region of Colombia.\n72 We hypothesize that integrating metataxonomic profiling of the 18S rDNA V4 region  with \n73 phylogenetic inference based on concatenated 18S–28S reference sequences enhances detection \n74 sensitivity and provides a versatile framework for identifying nematodes across heterogeneous \n75 environmental matrices. This approach enables robust taxonomic assignment and detection of \n76 morphologically cryptic and environmentally persistent taxa [17,22], while supporting the \n77 development of scalable molecular protocols for parasite surveillance within wastewater-based \n78 epidemiology and One Health frameworks.\n79 MATERIALS AND METHODS\n80 Sample Collection and DNA Extraction\n81 Environmental samples were collected from four wastewater treatment plants \n82 (WWTPs), as well as from artisanal bioinputs and food sources. A total of 12 samples from \n83 WWTPs were obtained. The selected WWTPs are located in the Andean region, at elevations \n84 ranging from 1,080 meters above sea level (m a.s.l.) in Cali to 2,175 m a.s.l. [18]. The selected \n85 WWTPs collectively serve an estimated population of 5.5 million inhabitants. Two of these \n86 facilities San Fernando and Aguas Claras are situated in the Aburrá Valley metropolitan area \n87 and provide services to both the city and neighboring municipalities. The third plant, \n88 Cañaveralejo, is located in the city of Cali, while the fourth, El Retiro, is a smaller-scale facility \n89 serving a rural community in the municipality of El Retiro. \n90 Three food samples from the Aburrá Valley and five organic bioinput samples from the \n91 cities of Cali and Medellín were processed using the same extraction protocol during 2023 and \n92 2024, respectively.\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint \n\n5\n93 Prior to extraction, samples were homogenized using sterile instruments. DNA \n94 extraction was performed using the QIAGEN DNeasy PowerSoil Kit, processing 200 mg \n95 aliquots of environmental samples. The concentration and quality of purified DNA was \n96 determined by UV spectrophotometry, and samples were cryopreserved at −20 °C until use for \n97 PCR amplification [18]. \n98 Metataxonomic Analysis\n99 For DNA amplification, degenerate primers were used, designed to target the \n100 hypervariable V4 region of the eukaryotic 18S ribosomal gene (18S rDNA). The forward primer \n101 corresponded to the sequence 18S-V4Fw: (CCAGCAGCCGCGGTAATTCC) [23], the reverse \n102 primer used was 18S-V4Rev (RCYTTCGYYCTTGATTRA). These primers were successfully \n103 applied to the same sample set [18], in a study focused on protists. PCR amplification, genomic \n104 library preparation, and high-throughput sequencing services were outsourced to Macrogen Inc. \n105 (Seoul, South Korea), using the Illumina MiSeq platform configured for 300 bp paired-end \n106 reads.\n107 Bioinformatic processing of the obtained sequences was performed using MOTHUR \n108 (v.1.44.3), following the protocol described by Rozo-Montoya et al. (2023). This process \n109 included the merging of paired-end reads, filtering of sequences containing ambiguous bases \n110 or shorter than 300 bp, removal of sequences with homopolymers longer than eight bases, \n111 clustering by sequence similarity, detection and removal of chimeric sequences, and \n112 construction of molecular operational taxonomic units (mOTUs) using a 97% similarity \n113 threshold.\n114 Preliminary taxonomic assignment of the mOTUs was performed using the classify.seqs \n115 algorithm implemented in MOTHUR, with the SILVA (v.138) database serving as the \n116 reference [24]. Only mOTUs classified as eukaryotic were selected for subsequent BLASTn \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint \n\n6\n117 analysis [25], and phylogenetic studies. Sequencing quality indicators, including the number of \n118 high-quality sequences, mOTUs counts, and coverage estimators, were calculated using the \n119 summary.single command in MOTHUR. The raw amplicon sequences have been deposited in \n120 the NCBI SRA database under the Bioproject accession PRJNA976754.\n121 Species Selection and Bioinformatic Processing\n122 For this analysis, nematodes of public health importance were selected, including \n123 species parasitic to humans, zoonotic species, [26,27]. In total, the reference database \n124 incorporated 49 species represented across 27 genera.\n125 To obtain complete and high-quality rDNA sequences, nematode reference genomes of \n126 target species were downloaded from the NCBI database using its available datasets and a \n127 bioinformatic routine optimized for batch downloading. When no reference genome was \n128 available for a species of interest, complementary RNA-seq data were obtained from the NCBI \n129 Sequence Read Archive (SRA), followed by the extraction of contigs containing rDNA gene \n130 sequences using the Trinity program [28]. Neither genomic nor RNA-seq data were available \n131 for Strongyloides ransomi, instead partial 18S rDNA sequences (AB453327, OP288111) were \n132 included.\n133 From the reference genomes, an annotation and extraction strategy was implemented to \n134 specifically retrieve the 18S and 28S ribosomal regions using Barrnap (v0.9) [29], combined \n135 with an auxiliary bioinformatic pipeline. The annotated and extracted sequences underwent \n136 quality screening to remove ambiguous, fragmented, or incomplete sequences. Only sequences \n137 with a combined length ≥ 1,400 bp across the 18S and 28S regions were retained. From the \n138 filtered set, a single consensus sequence with the highest overall quality and length was \n139 selected.\n140 The resulting rDNA sequences were subjected to inspection and curation, including \n141 verification of orientation and length, format standardization, and consistent identifier \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint \n\n7\n142 assignment to ensure proper handling in subsequent analyses with SeqKit (v2.10.1) [30]. The \n143 18S and 28S sequences were aligned separately using MAFFT (v7.215) [31], and the resulting \n144 alignments were inspected in AliView [32]. Finally, both alignment sets were concatenated \n145 using FASconCAT-G (v1.06.1) [33]. \n146 Phylogenetic Analysis Using 18S and 28S rDNA Markers\n147 To identify the putative nematode molecular operational taxonomic units (mOTUs) of \n148 interest in this study, a nucleotide identity–based search strategy was employed using BLASTn. \n149 For this purpose, the mOTUs generated with MOTHUR were compared against a local \n150 reference database containing concatenated 18S and 28S rDNA regions. mOTUs showing \n151 ≥95% sequence identity, representing the degree of match between aligned sequences, and a \n152 BLAST score ≥500, which reflects the overall quality and significance of the alignment \n153 according to the BLASTn algorithm, were considered valid candidates for phylogenetic \n154 analysis.\n155 Reference sequences of 18S and 28S rDNA, together with the V4 region of the 18S \n156 rDNA from the putative mOTUs identified through BLASTn, were aligned using MAFFT \n157 (v7.215). The resulting alignment was manually inspected to identify and correct potential \n158 conflicting regions using AliView. Subsequently, maximum likelihood (ML) phylogenetic \n159 trees were constructed with the aligned sequences using IQ-TREE3 [34]. The robustness of \n160 branch support was evaluated using a dual approach: Ultrafast Bootstrap (UFBoot) and the \n161 Approximate Likelihood Ratio Test (aLRT), both computed with 5,000 replicates.\n162 Data Management and Presentation\n163 Basic descriptive statistical analyses were performed using custom routines \n164 implemented in Python, including calculations of taxa presence–absence, occurrence \n165 frequencies, and genus- and species-level richness across samples and sampling sites. These \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint \n\n8\n166 summaries were used to support comparative interpretation of nematode diversity and \n167 distribution patterns.\n168 Phylogenetic trees were visualized and edited using FigTree (v1.4.4) [35], where tree \n169 topologies were examined and clades of interest were selectively collapsed to enhance \n170 interpretability. Branch coloring and additional graphical refinements were subsequently \n171 applied using image editing software.\n172 For graphical representation of spatial patterns, regional distribution maps were \n173 generated using QGIS (v3.40.11) [36]. Heatmaps summarizing taxa occurrence and relative \n174 abundance patterns were produced in R (v4.3.1) using the dplyr and ggplot2 packages.\n175 Results\n176 Construction of mOTUs and sequence processing\n177 In each amplicon library, a minimum of 109,906 pairs of raw reads were obtained, with \n178 a maximum of 334,064 reads per sample. After merging and quality-filtering processes, the \n179 number of retained high-quality sequences ranged from 37,705 to 77,967. The number of \n180 molecular operational taxonomic units (mOTUs) detected across samples varied between 374 \n181 and 866. The coverage index ranged from 99.4% to 99.7%, indicating a high level of sampling \n182 of the expected theoretical diversity. \n183 Construction of a local database from Genomes\n184 A total of 63 genomes representing 49 nematode species across 27 genera were analysed \n185 from the NCBI database. Genome sizes ranged from 42.5 to 656.4 Mb (median: 111.8 Mb).\n186 Assembly continuity (N50) varied from 1.2 kb to 110.8 Mb (median: 1,095.2 kb), while \n187 fragmentation ranged from 2 to 167,310 contigs (median: 651). GC content ranged between \n188 21.30% and 47.96% (mean: 36.68%). Most assemblies showed low levels of ambiguous bases \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint \n\n9\n189 (median: 0.33%), although higher values were observed in Oesophagostomum dentatum, \n190 Romanomermis culicivorax, and Ancylostoma ceylanicum.\n191 The extraction of rDNA sequences using Barrnap was highly effective, achieving a \n192 success rate of 98.4% (62 out of 63 analyzed genomes). The only exception corresponded to \n193 Enterobius vermicularis (GCA_900576705), for which the software failed to identify ribosomal \n194 regions; thus, the dataset was complemented with nucleotide sequences obtained through partial \n195 RNA-seq annotation from assembly SRA_ERR310935 and Sanger sequences (FR687850, \n196 AF182295, JF934731, LC416069). A total of 14,875 rDNA sequences were recovered from \n197 genomes using this methodology: 6,276 corresponding to 18S and 8,599 to 28S. The \n198 concatenated consensus sequences (18S + 28S) ranged in length from 1,448 to 8,682 bp, with \n199 an average length of 4,925 bp, while the percentage of ambiguous nucleotides remained ≤ \n200 0.03% in all cases. \n201 Taxonomic assignment of mOTUs by phylogenetic inference of \n202 rDNA.\n203 The initial analysis performed with MOTHUR generated a total of 16,045 mOTUs. \n204 Subsequently, the nucleotide identity search using BLASTn against the local reference database \n205 enabled the recovery of 933 hits that met the established filtering criteria (identity ≥ 95% and \n206 score ≥ 500). After removing redundant hits, 292 representative sequences were retained. These \n207 candidate sequences were aligned with MAFFT alongside the consensus reference sequences \n208 and subjected to phylogenetic inference. The general description of nematode genus per sample \n209 is described in Fig 1.\n210 The maximum likelihood of phylogenetic analyses represented by the 25 mOTUs \n211 retained after filtering. The phylogenetic reconstruction of the nematodes of interest in this \n212 study showed high levels of statistical support, with UFBoot and aLRT values ≥ 95% for most \n213 clades, both calculated from 5,000 replicates. This degree of confidence allowed the \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint \n\n10\n214 consolidation of well-defined and clearly separated clades, consistent with previously reported \n215 phylogenetic structures described by other authors.[1,3,5,26]. Although it was necessary to \n216 supplement certain lineages not derived from reference genomes, the individual clade supports \n217 were sufficiently robust to allow a reliable assignment of the mOTUs included in the analysis.\n218 In Clade I, the presence of T. trichiura was confirmed with high phylogenetic support \n219 (UFBoot and aLRT ≥ 95%). For Trichinella spp. support values were slightly lower but still \n220 sufficient to enable reliable genus-level assignment. For Trichinella spp., phylogenetic analysis \n221 revealed clear separation from closely related species, with the mOTUs clustering within the \n222 clade comprising T. britovi and T. pseudospiralis (Fig 2).\n223 In Clade III, E. vermicularis was assigned with high confidence (UFBoot and aLRT ≥ \n224 95%) and represented by five mOTUs. For the genus Ascaris, phylogenetic resolution did not \n225 allow differentiation between A. suum and A. lumbricoides due to their close evolutionary \n226 relationship (Fig 3).\n227 In Clade IV, no species were confidently detected with support values above the \n228 significance threshold (UFBoot and aLRT ≥ 95%). Detailed results for this clade are therefore \n229 provided in the supplementary material (S1 Fig).\n230 Finally, in Clade V, A. cantonensis were assigned with robust support (UFBoot and \n231 aLRT ≥ 95%). For N. americanus, support was slightly lower, although clustering within a \n232 well-defined clade allowed confirmation of its taxonomic identity (Fig 4).\n233 Temporal Dynamics and Distribution of Nematode DNA in \n234 Wastewater Treatment Plants (WWTPs)\n235 The occasional presence of nematode DNA was observed in the WWTPs, showing defined \n236 spatial distribution patterns at each study site (Fig 5). In Aguas Claras WWTP, a consistent \n237 pattern of nematode DNA detection over time was observed. In the influent water from 2021 \n238 (sample K7F4002), Trichinella spp. were detected. The biosolids from this plant appeared to \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint \n\n11\n239 act as a reservoir, with N. americanus, Trichinella spp., and Ascaris spp., detected in the same \n240 year (samples K7B2001 and K7B2002). In the 2023 influent (sample M9F4003), Trichinella \n241 spp., and A. cantonensis were identified. In contrast, the biosolids for the same period (sample \n242 M9B2003) contained T. trichiura, Trichinella spp., N. americanus, and Ascaris spp. (Fig 5, S2 \n243 Fig).\n244 In San Fernando WWTP, during 2021, the influent water (sample K7F4004) contained \n245 E. vermicularis, and Trichinella spp. In the corresponding biosolid (sample K7B3001), A. \n246 cantonensis was detected, while the effluent showed no detectable nematode DNA (Fig 5, S3 \n247 Fig).\n248 In Cañaveralejo WWTP (Cali), biosolid analysis revealed the persistence of Ascaris \n249 spp., N. americanus, in sample K7B1001, and the detection of nematode DNA corresponding \n250 to N. americanus, and Trichinella spp. in sample K7B1002 (Fig 5, S4 Fig).\n251 Finally, in El Retiro WWTP, residual sludge (sample K7B4001) showed no detectable \n252 nematode DNA, whereas the effluent water (sample K7F4001) contained Trichinella spp., and \n253 A. cantonensis. (Fig 5, S5 Fig).\n254 Presence of Nematode DNA in Bioinputs and Foods\n255 In the analysis of commercial bioinputs, DNA from species of public health relevance \n256 was detected in samples N8C1002, N8C1003, and N8C2001, all of which tested positive for \n257 Trichinella spp. Specifically, sample N8C1002 also exhibited a more diverse parasitic \n258 community, with the detection of nematode DNA corresponding to N. americanus, and Ascaris \n259 spp. In N8C1001, N. americanus was additionally detected, while in sample N8C2001, N. \n260 americanus was identified in both samples.\n261 Regarding the food samples analyzed in 2023, only one sample (M9A2001) contained \n262 DNA corresponding to Trichinella spp. (Fig 6).\n263 Discussion\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint \n\n12\n264\n265 Wastewater-based epidemiological surveillance and relevance of \n266 nematodes as environmental markers\n267 Wastewater-based epidemiology (WBE) has emerged as an effective approach for \n268 monitoring the circulation of infectious agents within human populations, allowing the \n269 detection of pathogens shed into urban sanitation systems and providing an indirect \n270 representation of community-level infection dynamics [18,20]. Traditionally applied to viruses, \n271 bacteria, and protozoa, WBE is increasingly recognized as a promising framework for \n272 monitoring helminths of public health importance. In this context, the application of \n273 metataxonomic approaches enables the detection of nematode DNA in complex environmental \n274 matrices such as wastewater and biosolids, providing a scalable strategy for environmental \n275 parasite surveillance.\n276 In the present study, the detection of nematodes such as Trichuris trichiura, Ascaris \n277 spp., Enterobius vermicularis, and Necator americanus in wastewater treatment plants indicates \n278 that these systems act as environmental reservoirs of helminth DNA originating from human \n279 populations. The presence of these taxa is consistent with their known transmission routes, \n280 primarily associated with fecal contamination and inadequate sanitation [37]. The persistence \n281 of parasitic structures such as Ascaris and Trichuris eggs in wastewater systems has been widely \n282 documented due to their high environmental resistance and ability to accumulate in sludge and \n283 biosolids during treatment processes [38].\n284 The taxa detected in this study also correspond broadly with national epidemiological \n285 records. According to the National Survey of Intestinal Parasitism in the School Population \n286 2012–2014 (ENPI), the most frequently reported intestinal nematodes in Colombia are \n287 Trichuris trichiura, Ascaris lumbricoides, and hookworms (Necator americanus / Ancylostoma \n288 duodenale) [7]. The recurrent detection of T. trichiura, Ascaris spp., and N. americanus DNA \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint \n\n13\n289 in wastewater and biosolids therefore reflects the continued circulation of these geohelminths \n290 in the population and highlights their usefulness as indicators of fecal contamination and \n291 sanitation deficiencies. Notably, A. duodenale DNA was not detected in the analyzed samples, \n292 suggesting that in the studied regions the dominant hookworm component may correspond \n293 primarily to N. americanus.\n294 Beyond these well-known soil-transmitted helminths, the detection of zoonotic taxa \n295 such as Angiostrongylus cantonensis and and Trichinella spp. expands the spectrum of parasites \n296 identifiable through environmental molecular monitoring. A. cantonensis, an emerging \n297 zoonotic parasite in Latin America associated with human angiostrongyliasis and eosinophilic \n298 meningoencephalitis [39,40], was detected in multiple matrices in this study. Its presence in \n299 wastewater suggests potential environmental circulation mediated by intermediate hosts or \n300 contamination pathways not captured through conventional clinical surveillance.\n301 Taken together, these findings indicate that wastewater treatment systems function not \n302 only as sanitation infrastructures but also as environmental observatories for pathogen \n303 circulation. In Colombia, surveillance of soil-transmitted helminths remains largely focused on \n304 clinical reporting and periodic deworming campaigns, with limited integration of \n305 environmental data into public health monitoring systems. In this context, the metataxonomic \n306 detection of nematode DNA in wastewater provides an additional layer of information that \n307 could complement existing surveillance frameworks and support more proactive approaches to \n308 parasite monitoring within a One Health perspective.\n309 Bioinputs and food: parasitic risks in agricultural systems\n310 The increasing commercialization of agricultural bioinputs derived from organic residues has \n311 expanded their use as fertilizers, soil conditioners, and microbial amendments in both small-\n312 scale and industrial agricultural systems. These products, often produced from treated organic \n313 matter or recycled waste streams, are widely promoted as sustainable alternatives to \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint \n\n14\n314 conventional agrochemicals. However, when sanitary controls are insufficient or production \n315 processes are poorly standardized, bioinputs may act as vehicles for the persistence and \n316 dissemination of microorganisms and parasitic DNA across agricultural environments. In this \n317 context, the evaluation of commercially available bioinputs and their potential role in the \n318 environmental circulation of parasites becomes particularly relevant, especially when these \n319 products are applied to soils used for food production [38,41].\n320 Geohelminths, such as Ascaris spp., Trichuris trichiura, and Necator americanus, \n321 possess resistant structures that allow them to persist in environmental matrices such as water, \n322 soil, and biosolids. When these residues are used as bioinputs without proper treatment, the \n323 transmission cycle can be facilitated by contaminating agricultural soils and crops intended for \n324 human or animal consumption, thereby sustaining parasitic transmission cycles [38,41,42]. This \n325 dynamic perpetuates cross-contamination between the sanitation, agricultural, and food \n326 systems, creating an ecological circuit for parasitic persistence.\n327 Although biological and thermal treatments significantly reduce microbial loads, \n328 various studies have demonstrated the residual presence of oocysts, cysts, and parasitic DNA \n329 even after conventional purification processes, highlighting their structural resistance [41]. \n330 Therefore, the production and use of bioinputs derived from treated sludge should include \n331 advanced sanitization processes and effectiveness controls, aimed at interrupting parasite \n332 transmission cycles and reducing associated risks [38,43].\n333 In this regard, the safe management of bioinputs requires the integration of \n334 environmental, health, and food surveillance, ensuring that the reused residues do not pose a \n335 public health risk. Likewise, food represents a secondary exposure route, arising from the use \n336 of non-sanitized bioinputs for fertilization or from contact with contaminated environmental \n337 matrices, such as irrigation water. This connection underscores the need to assess parasitic \n338 traceability throughout the agri-food chain.\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint \n\n15\n339 Accordingly, the molecular monitoring of nematodes and other parasites in reused \n340 matrices constitutes a key tool to strengthen agricultural biosafety, protect community health, \n341 and promote sustainability in wastewater treatment and reuse systems [42].\n342 Reference databases and limitations for species-level identification\n343 The technical and technological feasibility of applying metataxonomic approaches to \n344 nematodes remains an emerging challenge. Although these methodologies are well established \n345 for bacteria and fungi, their development in parasites is still in its early stages. Nevertheless, \n346 the results obtained in this study demonstrate that it is possible to overcome, at least partially, \n347 the current limitations and move toward the standardization of specific protocols for the \n348 identification of nematodes in environmental matrices.\n349 In this study, the combined use of the hypervariable V4 region of the 18S rDNA gene \n350 and concatenated 18S–28S reference sequences provided consistent taxonomic resolution and \n351 sufficient phylogenetic support to resolve several taxa at the genus level and, in some cases, at \n352 the species level [6,11]. \n353 The construction of the local reference database, derived from complete genomes and \n354 curated ribosomal sequences, was a key component of this study and simultaneously \n355 represented one of the main methodological challenges. Although the taxonomic coverage \n356 achieved was close to 100% of the nematodes included, the limited availability of complete \n357 genomes in public databases remains a major constraint for large-scale, high-resolution \n358 phylogenetic studies [5,22], and the biases associated with species diversity coverage will \n359 remain latent until this gap is resolved.\n360 Through the strategy of annotating and extracting 18S and 28S ribosomal regions using \n361 Barrnap, more than 98% of the expected sequences were successfully recovered, generating 62 \n362 high-quality concatenated consensus sequences, which enabled the construction of a robust \n363 phylogenetic foundation. This advancement helps to address one of the most significant gaps \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint \n\n16\n364 in nematode metataxonomy: the lack of curated databases containing complete ribosomal \n365 information, which limits the taxonomic accuracy of inferences [22].\n366 The maximum likelihood analysis allowed the identification of 25 mOTUs with strong \n367 statistical support (UFBoot and aLRT ≥ 95%), distributed across four clades and six nematode \n368 taxa. The topological congruence observed between the trees generated in this study and \n369 previously reported nematode phylogenies reinforces the robustness and reliability of the \n370 taxonomic assignments obtained [1,3,5,6]. These results support the reliability of the \n371 concatenated ribosomal marker system for resolving both deep evolutionary relationships and \n372 recent divergences [3,5].\n373 The phylogenetic reconstruction confirmed the presence of six nematode taxa, several \n374 of which are of public health and zoonotic importance. Among the human intestinal nematodes, \n375 T. trichiura, E. vermicularis, and N. americanus were identified, all with high support values \n376 (≥ 95%).\n377 Despite these advances, intraspecific resolution remains limited, especially in genera \n378 such as Ascaris and Trichinella, which exhibit low genetic divergence among closely related \n379 species. In these cases, taxonomic assignment was restricted to the genus level (spp.) due to the \n380 inability to distinguish between closely related species (A. suum/A. lumbricoides, T. britovi/T. \n381 pseudospiralis). Such limitations are consistent with previous metataxonomic studies of \n382 nematodes, where the resolving power of rDNA is considered moderate, yet sufficient for \n383 genus-level identification and effective for epidemiological surveillance [12,22].\n384 This study demonstrates that ribosomal metataxonomics, when combined with \n385 phylogenetic validation using curated reference databases, constitutes a scalable framework for \n386 detecting parasitic nematode DNA across heterogeneous environmental matrices.\n387 Constraints and prospects\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint \n\n17\n388 Despite the high sensitivity and reproducibility of the approach employed, intraspecific \n389 taxonomic resolution remains a challenge, particularly for lineages with low genetic divergence \n390 or highly conserved ribosomal sequences. Moreover, the detection of DNA does not necessarily \n391 imply the presence of viable or infectious organisms, so results should be interpreted in an \n392 ecological context, not solely at the molecular level.\n393 The aim of this study was not to estimate parasite prevalence but to evaluate the \n394 feasibility of a metataxonomic framework for environmental surveillance across heterogeneous \n395 environmental matrices. Consequently, the results should be interpreted as evidence of \n396 methodological applicability rather than as a direct measure of parasite burden in the studied \n397 populations.\n398 Future research should integrate higher-resolution markers, as well as phylogenomic \n399 strategies that allow more precise identification of cryptic and emerging species. Likewise, \n400 coupling spatial and temporal analyses could facilitate correlations between the presence of \n401 nematode DNA and local environmental or sanitary variables, thereby strengthening the \n402 predictive capacity of wastewater-based molecular surveillance.\n403\n404 Figure legends\n405 Fig 1. National and regional map of the Andean zone of Colombia showing all sampling \n406 locations included in the study. Coloured markers indicate the sites where nematode DNA \n407 was detected in wastewater treatment plants (WWTPs), biofertilizers, and food items collected \n408 between 2021 and 2024. This figure illustrates the geographic distribution of nematode \n409 presence, highlighting both urban and peri-urban areas. It provides a visual overview of the \n410 spatial heterogeneity of nematode contamination and identifies hotspots for potential \n411 epidemiological monitoring.\n412 Fig 2. Phylogenetic analysis of Clade I for taxonomic assignment. Maximum-likelihood \n413 phylogenetic tree of Clade I, based on concatenated rDNA sequences (18S + 28S). Molecular \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint \n\n18\n414 operational taxonomic units (mOTUs) identified in the samples are labeled on the tree. High \n415 support values (UFBoot and aLRT ≥ 95 %) demonstrate the reliability of genus-level and, in \n416 some cases, species-level assignments. This clade includes nematodes of clinical and zoonotic \n417 relevance, supporting the utility of molecular monitoring in environmental matrices.\n418 Fig 3. Phylogenetic analysis of Clade III for taxonomic assignment. Maximum-likelihood \n419 phylogenetic tree of Clade III, showing the placement of mOTUs identified in the study. The \n420 figure highlights intra-clade diversity and reveals phylogenetic relationships among nematodes \n421 present in wastewater and biofertilizer samples. Branch support values indicate the robustness \n422 of the assignments and provide confidence in interpreting potential transmission pathways.\n423 Fig 4. Phylogenetic analysis of Clade V for taxonomic assignment.Maximum-likelihood \n424 phylogenetic tree of Clade V, illustrating the placement of mOTUs detected in environmental \n425 samples. Support values (UFBoot and aLRT from 5,000 replicates) demonstrate reliable \n426 phylogenetic inference. This clade includes nematodes with varying degrees of public health \n427 significance, highlighting the importance of environmental surveillance for both human and \n428 zoonotic pathogens.\n429 Fig 5. Comparative heatmaps of nematode DNA detection across wastewater treatment \n430 plants. Heatmaps illustrate the presence and absence of nematode DNA across all analyzed \n431 matrices between 2021 and 2024. Wastewater treatment plants (WWTPs), showing spatial and \n432 temporal patterns of detection and identifying facilities that act as persistent reservoirs of \n433 nematode genetic material (* indicates samples collected in 2023). \n434 Fig 6. Comparative heatmaps of nematode DNA detection across biofertilizers, and food \n435 samples. Commercial biofertilizers and food items, evidencing potential parasite transmission \n436 routes through the reuse of treated or untreated biosolids in agriculture (* samples from 2023; \n437 ** from 2024).\n438\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint \n\n19\n439\n440 Supporting information\n441\n442 S1 Fig Phylogenetic analysis of Clade IV for taxonomic assignment. Maximum-likelihood \n443 phylogenetic tree of Clade I.\n444 S2 Fig Comparative heatmaps of nematode DNA detection across wastewater treatment \n445 plants. Aguas Claras.\n446 S3 Fig Comparative heatmaps of nematode DNA detection across wastewater treatment \n447 plants. San Fernando.\n448 S4 Fig Comparative heatmaps of nematode DNA detection across wastewater treatment \n449 plants. Cañaveralejo\n450 S5 Fig Comparative heatmaps of nematode DNA detection across wastewater treatment \n451 plants. El Retiro.\n452 References \n453 1. Koutsovoulos GD. Reconstructing the phylogenetic relationships of nematodes using draft \n454 genomes and transcriptomes [dissertation]. Edinburgh: University of Edinburgh; 2015. \n455 http://hdl.handle.net/1842/10558\n456 2. Smythe AB, Holovachov O, Kocot KM. Improved phylogenomic sampling of free-living \n457 nematodes enhances resolution of higher-level nematode phylogeny. BMC Evol Biol. \n458 2019;19(1):121. https://doi.org/10.1186/s12862-019-1444-x\n459 3. Ahmed M, Roberts NG, Adediran F, Smythe AB, Kocot KM, Holovachov O. Phylogenomic \n460 analysis of the phylum Nematoda: conflicts and congruences with morphology, 18S rRNA, \n461 and mitogenomes. 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Land application of municipal sewage sludge: human \n581 health risk assessment of heavy metals. J Clean Prod. 2021;319:128568. \n582 https://doi.org/10.1016/j.jclepro.2021.128568\n583 43. Laura F, Tamara A, Müller A, Hiroshan H, Christina D, Serena C. Selecting sustainable \n584 sewage sludge reuse options through a systematic assessment framework: methodology and \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint \n\n23\n585 case study in Latin America. J Clean Prod. 2020;242:118389. \n586 https://doi.org/10.1016/j.jclepro.2019.118389\n587\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint \n\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint \n\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint \n\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint \n\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint \n\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint \n\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint","source_license":"CC-BY-4.0","license_restricted":false}