A Ribosomal Marker-Based Metataxonomic Framework for Environmental Surveillance of Nematodes of Public Health Importance

1 1 A Ribosomal Marker-Based Metataxonomic Framework 2 for Environmental Surveillance of Nematodes of Public 3 Health Importance 4 5 Juan P. Zuluaga1, Katherine Bedoya-Urrego2, Juan F. Alzate 2,3,* 6 7 1Escuela de Microbiología, Universidad de Antioquia, Medellín, Colombia. 8 2Centro de Secuenciación Genómica (CNSG), Sede de Investigación Universitaria (SIU), 9 Universidad de Antioquia, Medellín, Colombia. 10 3Departamento de Microbiología y Parasitología, Facultad de Medicina, Universidad de 11 Antioquia, Medellín, Colombia. 12 13 *Corresponding author: 14 [email protected] 15 16 17 18 19 20 21 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.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 The copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint 2 22 ABSTRACT 23 Metataxonomic analysis targeting the V4 region of the 18S rDNA gene, combined with 24 molecular phylogenetic inference, was applied to detect nematode DNA of public health 25 relevance in environmental matrices. A total of 25 mOTUs corresponding to six nematode taxa 26 were detected in environmental samples from the Andean region of Colombia. Analysis of 12 27 water and sludge samples from wastewater treatment plants, 5 artisanal agricultural bioinputs, 28 and 3 food samples revealed multiple species of public health significance: Trichuris trichiura, 29 Enterobius vermicularis, Ascaris spp., and Necator americanus. We also confirmed zoonotic 30 species, including Angiostrongylus cantonensis and Trichinella spp. These findings 31 demonstrate that combining metataxonomics with molecular phylogeny provides a scalable 32 molecular framework for the environmental surveillance of parasitic nematodes, overcoming 33 the limitations of traditional morphological identification methods . This approach offers a 34 replicable model for strengthening control and monitoring programs for parasitism in human 35 populations. 36 KEYWORDS Nematodes; Metataxonomics; Phylogenetics; Sludge; Wastewater; 37 Bioinputs; Food 38 INTRODUCTION 39 Nematodes are ubiquitous metazoans found in terrestrial and aquatic habitats, 40 parasitizing plants and animals including humans [1,2]. Approximately 30,000 species have 41 been described, though total diversity may approach one million [3–5]. They exhibit remarkable 42 trophic diversity, feeding on bacteria, fungi, algae, protozoa, and other nematodes, or living as 43 facultative or obligate parasites [5,6]. In Colombia, nematode infections pose a significant public 44 health problem, particularly among children [7], compounded by emerging anthelmintic .CC-BY 4.0 International licensemade available under a (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 The copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint 3 45 resistance in both animal and human nematodes [8,9]. Intensive antiparasitic drug use has been 46 selected for resistant organisms, compromising control programs [10], necessitating more 47 sensitive molecular identification approaches. 48 Nematode species identification typically relies on morphological characteristics of 49 adults, larvae, and eggs [11,12]. However, classical methods often produce nonspecific 50 identifications, underestimating parasite circulation [6,12,13]. For instance, adult and larvae 51 morphological similarities in mouthpart, esophagus and tail structures can obscure distinctions 52 between species, and variations in body length may not adequately reflect species differences 53 due to overlapping size ranges. Taxonomic resolution is frequently limited to genus level; for 54 example, hookworm egg observation cannot differentiate Necator americanus from 55 Ancylostoma duodenale [14]. Despite their ecological and physiological diversity, nematodes 56 conserved morphology and small size provide few phylogenetically informative characters, 57 many showing convergent evolution [6]. In environmental samples, clinically relevant 58 nematode eggs may be misidentified as Acari (mite) eggs due to morphological similarities, 59 potentially leading to diagnostic errors [15]. 60 Conventional diagnostic methods cannot adequately detect parasitic nematode diversity 61 [6]. In previous studies, metataxonomic approaches targeting ribosomal rDNA regions have 62 demonstrated high sensitivity and specificity for cryptic or closely related species [16–18]. 63 Though taxonomic resolution may be limited to genus level, metataxonomics offers 64 reproducibility, scalability, automation, and cost-effectiveness [17], and facilitates parasite 65 detection in complex environmental matrices [18]. While widely applied in prokaryotes [19–21], 66 nematode metataxonomic studies remain emerging [3,22]. 67 Accurate detection of parasitic nematodes in environmental matrices is critical for 68 environmental surveillance and public health monitoring, yet remains constrained by limitations 69 in sensitivity and taxonomic resolution. To address these challenges, this study implements .CC-BY 4.0 International licensemade available under a (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 The copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint 4 70 metataxonomics coupled with phylogenetic analyses to detect nematodes of public health 71 importance in environmental samples from the Andean region of Colombia. 72 We hypothesize that integrating metataxonomic profiling of the 18S rDNA V4 region with 73 phylogenetic inference based on concatenated 18S–28S reference sequences enhances detection 74 sensitivity and provides a versatile framework for identifying nematodes across heterogeneous 75 environmental matrices. This approach enables robust taxonomic assignment and detection of 76 morphologically cryptic and environmentally persistent taxa [17,22], while supporting the 77 development of scalable molecular protocols for parasite surveillance within wastewater-based 78 epidemiology and One Health frameworks. 79 MATERIALS AND METHODS 80 Sample Collection and DNA Extraction 81 Environmental samples were collected from four wastewater treatment plants 82 (WWTPs), as well as from artisanal bioinputs and food sources. A total of 12 samples from 83 WWTPs were obtained. The selected WWTPs are located in the Andean region, at elevations 84 ranging from 1,080 meters above sea level (m a.s.l.) in Cali to 2,175 m a.s.l. [18]. The selected 85 WWTPs collectively serve an estimated population of 5.5 million inhabitants. Two of these 86 facilities San Fernando and Aguas Claras are situated in the Aburrá Valley metropolitan area 87 and provide services to both the city and neighboring municipalities. The third plant, 88 Cañaveralejo, is located in the city of Cali, while the fourth, El Retiro, is a smaller-scale facility 89 serving a rural community in the municipality of El Retiro. 90 Three food samples from the Aburrá Valley and five organic bioinput samples from the 91 cities of Cali and Medellín were processed using the same extraction protocol during 2023 and 92 2024, respectively. .CC-BY 4.0 International licensemade available under a (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 The copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint 5 93 Prior to extraction, samples were homogenized using sterile instruments. DNA 94 extraction was performed using the QIAGEN DNeasy PowerSoil Kit, processing 200 mg 95 aliquots of environmental samples. The concentration and quality of purified DNA was 96 determined by UV spectrophotometry, and samples were cryopreserved at −20 °C until use for 97 PCR amplification [18]. 98 Metataxonomic Analysis 99 For DNA amplification, degenerate primers were used, designed to target the 100 hypervariable V4 region of the eukaryotic 18S ribosomal gene (18S rDNA). The forward primer 101 corresponded to the sequence 18S-V4Fw: (CCAGCAGCCGCGGTAATTCC) [23], the reverse 102 primer used was 18S-V4Rev (RCYTTCGYYCTTGATTRA). These primers were successfully 103 applied to the same sample set [18], in a study focused on protists. PCR amplification, genomic 104 library preparation, and high-throughput sequencing services were outsourced to Macrogen Inc. 105 (Seoul, South Korea), using the Illumina MiSeq platform configured for 300 bp paired-end 106 reads. 107 Bioinformatic processing of the obtained sequences was performed using MOTHUR 108 (v.1.44.3), following the protocol described by Rozo-Montoya et al. (2023). This process 109 included the merging of paired-end reads, filtering of sequences containing ambiguous bases 110 or shorter than 300 bp, removal of sequences with homopolymers longer than eight bases, 111 clustering by sequence similarity, detection and removal of chimeric sequences, and 112 construction of molecular operational taxonomic units (mOTUs) using a 97% similarity 113 threshold. 114 Preliminary taxonomic assignment of the mOTUs was performed using the classify.seqs 115 algorithm implemented in MOTHUR, with the SILVA (v.138) database serving as the 116 reference [24]. Only mOTUs classified as eukaryotic were selected for subsequent BLASTn .CC-BY 4.0 International licensemade available under a (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 The copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint 6 117 analysis [25], and phylogenetic studies. Sequencing quality indicators, including the number of 118 high-quality sequences, mOTUs counts, and coverage estimators, were calculated using the 119 summary.single command in MOTHUR. The raw amplicon sequences have been deposited in 120 the NCBI SRA database under the Bioproject accession PRJNA976754. 121 Species Selection and Bioinformatic Processing 122 For this analysis, nematodes of public health importance were selected, including 123 species parasitic to humans, zoonotic species, [26,27]. In total, the reference database 124 incorporated 49 species represented across 27 genera. 125 To obtain complete and high-quality rDNA sequences, nematode reference genomes of 126 target species were downloaded from the NCBI database using its available datasets and a 127 bioinformatic routine optimized for batch downloading. When no reference genome was 128 available for a species of interest, complementary RNA-seq data were obtained from the NCBI 129 Sequence Read Archive (SRA), followed by the extraction of contigs containing rDNA gene 130 sequences using the Trinity program [28]. Neither genomic nor RNA-seq data were available 131 for Strongyloides ransomi, instead partial 18S rDNA sequences (AB453327, OP288111) were 132 included. 133 From the reference genomes, an annotation and extraction strategy was implemented to 134 specifically retrieve the 18S and 28S ribosomal regions using Barrnap (v0.9) [29], combined 135 with an auxiliary bioinformatic pipeline. The annotated and extracted sequences underwent 136 quality screening to remove ambiguous, fragmented, or incomplete sequences. Only sequences 137 with a combined length ≥ 1,400 bp across the 18S and 28S regions were retained. From the 138 filtered set, a single consensus sequence with the highest overall quality and length was 139 selected. 140 The resulting rDNA sequences were subjected to inspection and curation, including 141 verification of orientation and length, format standardization, and consistent identifier .CC-BY 4.0 International licensemade available under a (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 The copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint 7 142 assignment to ensure proper handling in subsequent analyses with SeqKit (v2.10.1) [30]. The 143 18S and 28S sequences were aligned separately using MAFFT (v7.215) [31], and the resulting 144 alignments were inspected in AliView [32]. Finally, both alignment sets were concatenated 145 using FASconCAT-G (v1.06.1) [33]. 146 Phylogenetic Analysis Using 18S and 28S rDNA Markers 147 To identify the putative nematode molecular operational taxonomic units (mOTUs) of 148 interest in this study, a nucleotide identity–based search strategy was employed using BLASTn. 149 For this purpose, the mOTUs generated with MOTHUR were compared against a local 150 reference database containing concatenated 18S and 28S rDNA regions. mOTUs showing 151 ≥95% sequence identity, representing the degree of match between aligned sequences, and a 152 BLAST score ≥500, which reflects the overall quality and significance of the alignment 153 according to the BLASTn algorithm, were considered valid candidates for phylogenetic 154 analysis. 155 Reference sequences of 18S and 28S rDNA, together with the V4 region of the 18S 156 rDNA from the putative mOTUs identified through BLASTn, were aligned using MAFFT 157 (v7.215). The resulting alignment was manually inspected to identify and correct potential 158 conflicting regions using AliView. Subsequently, maximum likelihood (ML) phylogenetic 159 trees were constructed with the aligned sequences using IQ-TREE3 [34]. The robustness of 160 branch support was evaluated using a dual approach: Ultrafast Bootstrap (UFBoot) and the 161 Approximate Likelihood Ratio Test (aLRT), both computed with 5,000 replicates. 162 Data Management and Presentation 163 Basic descriptive statistical analyses were performed using custom routines 164 implemented in Python, including calculations of taxa presence–absence, occurrence 165 frequencies, and genus- and species-level richness across samples and sampling sites. These .CC-BY 4.0 International licensemade available under a (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 The copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint 8 166 summaries were used to support comparative interpretation of nematode diversity and 167 distribution patterns. 168 Phylogenetic trees were visualized and edited using FigTree (v1.4.4) [35], where tree 169 topologies were examined and clades of interest were selectively collapsed to enhance 170 interpretability. Branch coloring and additional graphical refinements were subsequently 171 applied using image editing software. 172 For graphical representation of spatial patterns, regional distribution maps were 173 generated using QGIS (v3.40.11) [36]. Heatmaps summarizing taxa occurrence and relative 174 abundance patterns were produced in R (v4.3.1) using the dplyr and ggplot2 packages. 175 Results 176 Construction of mOTUs and sequence processing 177 In each amplicon library, a minimum of 109,906 pairs of raw reads were obtained, with 178 a maximum of 334,064 reads per sample. After merging and quality-filtering processes, the 179 number of retained high-quality sequences ranged from 37,705 to 77,967. The number of 180 molecular operational taxonomic units (mOTUs) detected across samples varied between 374 181 and 866. The coverage index ranged from 99.4% to 99.7%, indicating a high level of sampling 182 of the expected theoretical diversity. 183 Construction of a local database from Genomes 184 A total of 63 genomes representing 49 nematode species across 27 genera were analysed 185 from the NCBI database. Genome sizes ranged from 42.5 to 656.4 Mb (median: 111.8 Mb). 186 Assembly continuity (N50) varied from 1.2 kb to 110.8 Mb (median: 1,095.2 kb), while 187 fragmentation ranged from 2 to 167,310 contigs (median: 651). GC content ranged between 188 21.30% and 47.96% (mean: 36.68%). Most assemblies showed low levels of ambiguous bases .CC-BY 4.0 International licensemade available under a (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 The copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint 9 189 (median: 0.33%), although higher values were observed in Oesophagostomum dentatum, 190 Romanomermis culicivorax, and Ancylostoma ceylanicum. 191 The extraction of rDNA sequences using Barrnap was highly effective, achieving a 192 success rate of 98.4% (62 out of 63 analyzed genomes). The only exception corresponded to 193 Enterobius vermicularis (GCA_900576705), for which the software failed to identify ribosomal 194 regions; thus, the dataset was complemented with nucleotide sequences obtained through partial 195 RNA-seq annotation from assembly SRA_ERR310935 and Sanger sequences (FR687850, 196 AF182295, JF934731, LC416069). A total of 14,875 rDNA sequences were recovered from 197 genomes using this methodology: 6,276 corresponding to 18S and 8,599 to 28S. The 198 concatenated consensus sequences (18S + 28S) ranged in length from 1,448 to 8,682 bp, with 199 an average length of 4,925 bp, while the percentage of ambiguous nucleotides remained ≤ 200 0.03% in all cases. 201 Taxonomic assignment of mOTUs by phylogenetic inference of 202 rDNA. 203 The initial analysis performed with MOTHUR generated a total of 16,045 mOTUs. 204 Subsequently, the nucleotide identity search using BLASTn against the local reference database 205 enabled the recovery of 933 hits that met the established filtering criteria (identity ≥ 95% and 206 score ≥ 500). After removing redundant hits, 292 representative sequences were retained. These 207 candidate sequences were aligned with MAFFT alongside the consensus reference sequences 208 and subjected to phylogenetic inference. The general description of nematode genus per sample 209 is described in Fig 1. 210 The maximum likelihood of phylogenetic analyses represented by the 25 mOTUs 211 retained after filtering. The phylogenetic reconstruction of the nematodes of interest in this 212 study showed high levels of statistical support, with UFBoot and aLRT values ≥ 95% for most 213 clades, both calculated from 5,000 replicates. This degree of confidence allowed the .CC-BY 4.0 International licensemade available under a (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 The copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint 10 214 consolidation of well-defined and clearly separated clades, consistent with previously reported 215 phylogenetic structures described by other authors.[1,3,5,26]. Although it was necessary to 216 supplement certain lineages not derived from reference genomes, the individual clade supports 217 were sufficiently robust to allow a reliable assignment of the mOTUs included in the analysis. 218 In Clade I, the presence of T. trichiura was confirmed with high phylogenetic support 219 (UFBoot and aLRT ≥ 95%). For Trichinella spp. support values were slightly lower but still 220 sufficient to enable reliable genus-level assignment. For Trichinella spp., phylogenetic analysis 221 revealed clear separation from closely related species, with the mOTUs clustering within the 222 clade comprising T. britovi and T. pseudospiralis (Fig 2). 223 In Clade III, E. vermicularis was assigned with high confidence (UFBoot and aLRT ≥ 224 95%) and represented by five mOTUs. For the genus Ascaris, phylogenetic resolution did not 225 allow differentiation between A. suum and A. lumbricoides due to their close evolutionary 226 relationship (Fig 3). 227 In Clade IV, no species were confidently detected with support values above the 228 significance threshold (UFBoot and aLRT ≥ 95%). Detailed results for this clade are therefore 229 provided in the supplementary material (S1 Fig). 230 Finally, in Clade V, A. cantonensis were assigned with robust support (UFBoot and 231 aLRT ≥ 95%). For N. americanus, support was slightly lower, although clustering within a 232 well-defined clade allowed confirmation of its taxonomic identity (Fig 4). 233 Temporal Dynamics and Distribution of Nematode DNA in 234 Wastewater Treatment Plants (WWTPs) 235 The occasional presence of nematode DNA was observed in the WWTPs, showing defined 236 spatial distribution patterns at each study site (Fig 5). In Aguas Claras WWTP, a consistent 237 pattern of nematode DNA detection over time was observed. In the influent water from 2021 238 (sample K7F4002), Trichinella spp. were detected. The biosolids from this plant appeared to .CC-BY 4.0 International licensemade available under a (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 The copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint 11 239 act as a reservoir, with N. americanus, Trichinella spp., and Ascaris spp., detected in the same 240 year (samples K7B2001 and K7B2002). In the 2023 influent (sample M9F4003), Trichinella 241 spp., and A. cantonensis were identified. In contrast, the biosolids for the same period (sample 242 M9B2003) contained T. trichiura, Trichinella spp., N. americanus, and Ascaris spp. (Fig 5, S2 243 Fig). 244 In San Fernando WWTP, during 2021, the influent water (sample K7F4004) contained 245 E. vermicularis, and Trichinella spp. In the corresponding biosolid (sample K7B3001), A. 246 cantonensis was detected, while the effluent showed no detectable nematode DNA (Fig 5, S3 247 Fig). 248 In Cañaveralejo WWTP (Cali), biosolid analysis revealed the persistence of Ascaris 249 spp., N. americanus, in sample K7B1001, and the detection of nematode DNA corresponding 250 to N. americanus, and Trichinella spp. in sample K7B1002 (Fig 5, S4 Fig). 251 Finally, in El Retiro WWTP, residual sludge (sample K7B4001) showed no detectable 252 nematode DNA, whereas the effluent water (sample K7F4001) contained Trichinella spp., and 253 A. cantonensis. (Fig 5, S5 Fig). 254 Presence of Nematode DNA in Bioinputs and Foods 255 In the analysis of commercial bioinputs, DNA from species of public health relevance 256 was detected in samples N8C1002, N8C1003, and N8C2001, all of which tested positive for 257 Trichinella spp. Specifically, sample N8C1002 also exhibited a more diverse parasitic 258 community, with the detection of nematode DNA corresponding to N. americanus, and Ascaris 259 spp. In N8C1001, N. americanus was additionally detected, while in sample N8C2001, N. 260 americanus was identified in both samples. 261 Regarding the food samples analyzed in 2023, only one sample (M9A2001) contained 262 DNA corresponding to Trichinella spp. (Fig 6). 263 Discussion .CC-BY 4.0 International licensemade available under a (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 The copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint 12 264 265 Wastewater-based epidemiological surveillance and relevance of 266 nematodes as environmental markers 267 Wastewater-based epidemiology (WBE) has emerged as an effective approach for 268 monitoring the circulation of infectious agents within human populations, allowing the 269 detection of pathogens shed into urban sanitation systems and providing an indirect 270 representation of community-level infection dynamics [18,20]. Traditionally applied to viruses, 271 bacteria, and protozoa, WBE is increasingly recognized as a promising framework for 272 monitoring helminths of public health importance. In this context, the application of 273 metataxonomic approaches enables the detection of nematode DNA in complex environmental 274 matrices such as wastewater and biosolids, providing a scalable strategy for environmental 275 parasite surveillance. 276 In the present study, the detection of nematodes such as Trichuris trichiura, Ascaris 277 spp., Enterobius vermicularis, and Necator americanus in wastewater treatment plants indicates 278 that these systems act as environmental reservoirs of helminth DNA originating from human 279 populations. The presence of these taxa is consistent with their known transmission routes, 280 primarily associated with fecal contamination and inadequate sanitation [37]. The persistence 281 of parasitic structures such as Ascaris and Trichuris eggs in wastewater systems has been widely 282 documented due to their high environmental resistance and ability to accumulate in sludge and 283 biosolids during treatment processes [38]. 284 The taxa detected in this study also correspond broadly with national epidemiological 285 records. According to the National Survey of Intestinal Parasitism in the School Population 286 2012–2014 (ENPI), the most frequently reported intestinal nematodes in Colombia are 287 Trichuris trichiura, Ascaris lumbricoides, and hookworms (Necator americanus / Ancylostoma 288 duodenale) [7]. The recurrent detection of T. trichiura, Ascaris spp., and N. americanus DNA .CC-BY 4.0 International licensemade available under a (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 The copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint 13 289 in wastewater and biosolids therefore reflects the continued circulation of these geohelminths 290 in the population and highlights their usefulness as indicators of fecal contamination and 291 sanitation deficiencies. Notably, A. duodenale DNA was not detected in the analyzed samples, 292 suggesting that in the studied regions the dominant hookworm component may correspond 293 primarily to N. americanus. 294 Beyond these well-known soil-transmitted helminths, the detection of zoonotic taxa 295 such as Angiostrongylus cantonensis and and Trichinella spp. expands the spectrum of parasites 296 identifiable through environmental molecular monitoring. A. cantonensis, an emerging 297 zoonotic parasite in Latin America associated with human angiostrongyliasis and eosinophilic 298 meningoencephalitis [39,40], was detected in multiple matrices in this study. Its presence in 299 wastewater suggests potential environmental circulation mediated by intermediate hosts or 300 contamination pathways not captured through conventional clinical surveillance. 301 Taken together, these findings indicate that wastewater treatment systems function not 302 only as sanitation infrastructures but also as environmental observatories for pathogen 303 circulation. In Colombia, surveillance of soil-transmitted helminths remains largely focused on 304 clinical reporting and periodic deworming campaigns, with limited integration of 305 environmental data into public health monitoring systems. In this context, the metataxonomic 306 detection of nematode DNA in wastewater provides an additional layer of information that 307 could complement existing surveillance frameworks and support more proactive approaches to 308 parasite monitoring within a One Health perspective. 309 Bioinputs and food: parasitic risks in agricultural systems 310 The increasing commercialization of agricultural bioinputs derived from organic residues has 311 expanded their use as fertilizers, soil conditioners, and microbial amendments in both small- 312 scale and industrial agricultural systems. These products, often produced from treated organic 313 matter or recycled waste streams, are widely promoted as sustainable alternatives to .CC-BY 4.0 International licensemade available under a (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 The copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint 14 314 conventional agrochemicals. However, when sanitary controls are insufficient or production 315 processes are poorly standardized, bioinputs may act as vehicles for the persistence and 316 dissemination of microorganisms and parasitic DNA across agricultural environments. In this 317 context, the evaluation of commercially available bioinputs and their potential role in the 318 environmental circulation of parasites becomes particularly relevant, especially when these 319 products are applied to soils used for food production [38,41]. 320 Geohelminths, such as Ascaris spp., Trichuris trichiura, and Necator americanus, 321 possess resistant structures that allow them to persist in environmental matrices such as water, 322 soil, and biosolids. When these residues are used as bioinputs without proper treatment, the 323 transmission cycle can be facilitated by contaminating agricultural soils and crops intended for 324 human or animal consumption, thereby sustaining parasitic transmission cycles [38,41,42]. This 325 dynamic perpetuates cross-contamination between the sanitation, agricultural, and food 326 systems, creating an ecological circuit for parasitic persistence. 327 Although biological and thermal treatments significantly reduce microbial loads, 328 various studies have demonstrated the residual presence of oocysts, cysts, and parasitic DNA 329 even after conventional purification processes, highlighting their structural resistance [41]. 330 Therefore, the production and use of bioinputs derived from treated sludge should include 331 advanced sanitization processes and effectiveness controls, aimed at interrupting parasite 332 transmission cycles and reducing associated risks [38,43]. 333 In this regard, the safe management of bioinputs requires the integration of 334 environmental, health, and food surveillance, ensuring that the reused residues do not pose a 335 public health risk. Likewise, food represents a secondary exposure route, arising from the use 336 of non-sanitized bioinputs for fertilization or from contact with contaminated environmental 337 matrices, such as irrigation water. This connection underscores the need to assess parasitic 338 traceability throughout the agri-food chain. .CC-BY 4.0 International licensemade available under a (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 The copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint 15 339 Accordingly, the molecular monitoring of nematodes and other parasites in reused 340 matrices constitutes a key tool to strengthen agricultural biosafety, protect community health, 341 and promote sustainability in wastewater treatment and reuse systems [42]. 342 Reference databases and limitations for species-level identification 343 The technical and technological feasibility of applying metataxonomic approaches to 344 nematodes remains an emerging challenge. Although these methodologies are well established 345 for bacteria and fungi, their development in parasites is still in its early stages. Nevertheless, 346 the results obtained in this study demonstrate that it is possible to overcome, at least partially, 347 the current limitations and move toward the standardization of specific protocols for the 348 identification of nematodes in environmental matrices. 349 In this study, the combined use of the hypervariable V4 region of the 18S rDNA gene 350 and concatenated 18S–28S reference sequences provided consistent taxonomic resolution and 351 sufficient phylogenetic support to resolve several taxa at the genus level and, in some cases, at 352 the species level [6,11]. 353 The construction of the local reference database, derived from complete genomes and 354 curated ribosomal sequences, was a key component of this study and simultaneously 355 represented one of the main methodological challenges. Although the taxonomic coverage 356 achieved was close to 100% of the nematodes included, the limited availability of complete 357 genomes in public databases remains a major constraint for large-scale, high-resolution 358 phylogenetic studies [5,22], and the biases associated with species diversity coverage will 359 remain latent until this gap is resolved. 360 Through the strategy of annotating and extracting 18S and 28S ribosomal regions using 361 Barrnap, more than 98% of the expected sequences were successfully recovered, generating 62 362 high-quality concatenated consensus sequences, which enabled the construction of a robust 363 phylogenetic foundation. This advancement helps to address one of the most significant gaps .CC-BY 4.0 International licensemade available under a (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 The copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint 16 364 in nematode metataxonomy: the lack of curated databases containing complete ribosomal 365 information, which limits the taxonomic accuracy of inferences [22]. 366 The maximum likelihood analysis allowed the identification of 25 mOTUs with strong 367 statistical support (UFBoot and aLRT ≥ 95%), distributed across four clades and six nematode 368 taxa. The topological congruence observed between the trees generated in this study and 369 previously reported nematode phylogenies reinforces the robustness and reliability of the 370 taxonomic assignments obtained [1,3,5,6]. These results support the reliability of the 371 concatenated ribosomal marker system for resolving both deep evolutionary relationships and 372 recent divergences [3,5]. 373 The phylogenetic reconstruction confirmed the presence of six nematode taxa, several 374 of which are of public health and zoonotic importance. Among the human intestinal nematodes, 375 T. trichiura, E. vermicularis, and N. americanus were identified, all with high support values 376 (≥ 95%). 377 Despite these advances, intraspecific resolution remains limited, especially in genera 378 such as Ascaris and Trichinella, which exhibit low genetic divergence among closely related 379 species. In these cases, taxonomic assignment was restricted to the genus level (spp.) due to the 380 inability to distinguish between closely related species (A. suum/A. lumbricoides, T. britovi/T. 381 pseudospiralis). Such limitations are consistent with previous metataxonomic studies of 382 nematodes, where the resolving power of rDNA is considered moderate, yet sufficient for 383 genus-level identification and effective for epidemiological surveillance [12,22]. 384 This study demonstrates that ribosomal metataxonomics, when combined with 385 phylogenetic validation using curated reference databases, constitutes a scalable framework for 386 detecting parasitic nematode DNA across heterogeneous environmental matrices. 387 Constraints and prospects .CC-BY 4.0 International licensemade available under a (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 The copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint 17 388 Despite the high sensitivity and reproducibility of the approach employed, intraspecific 389 taxonomic resolution remains a challenge, particularly for lineages with low genetic divergence 390 or highly conserved ribosomal sequences. Moreover, the detection of DNA does not necessarily 391 imply the presence of viable or infectious organisms, so results should be interpreted in an 392 ecological context, not solely at the molecular level. 393 The aim of this study was not to estimate parasite prevalence but to evaluate the 394 feasibility of a metataxonomic framework for environmental surveillance across heterogeneous 395 environmental matrices. Consequently, the results should be interpreted as evidence of 396 methodological applicability rather than as a direct measure of parasite burden in the studied 397 populations. 398 Future research should integrate higher-resolution markers, as well as phylogenomic 399 strategies that allow more precise identification of cryptic and emerging species. Likewise, 400 coupling spatial and temporal analyses could facilitate correlations between the presence of 401 nematode DNA and local environmental or sanitary variables, thereby strengthening the 402 predictive capacity of wastewater-based molecular surveillance. 403 404 Figure legends 405 Fig 1. National and regional map of the Andean zone of Colombia showing all sampling 406 locations included in the study. Coloured markers indicate the sites where nematode DNA 407 was detected in wastewater treatment plants (WWTPs), biofertilizers, and food items collected 408 between 2021 and 2024. This figure illustrates the geographic distribution of nematode 409 presence, highlighting both urban and peri-urban areas. It provides a visual overview of the 410 spatial heterogeneity of nematode contamination and identifies hotspots for potential 411 epidemiological monitoring. 412 Fig 2. Phylogenetic analysis of Clade I for taxonomic assignment. Maximum-likelihood 413 phylogenetic tree of Clade I, based on concatenated rDNA sequences (18S + 28S). Molecular .CC-BY 4.0 International licensemade available under a (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 The copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint 18 414 operational taxonomic units (mOTUs) identified in the samples are labeled on the tree. High 415 support values (UFBoot and aLRT ≥ 95 %) demonstrate the reliability of genus-level and, in 416 some cases, species-level assignments. This clade includes nematodes of clinical and zoonotic 417 relevance, supporting the utility of molecular monitoring in environmental matrices. 418 Fig 3. Phylogenetic analysis of Clade III for taxonomic assignment. Maximum-likelihood 419 phylogenetic tree of Clade III, showing the placement of mOTUs identified in the study. The 420 figure highlights intra-clade diversity and reveals phylogenetic relationships among nematodes 421 present in wastewater and biofertilizer samples. Branch support values indicate the robustness 422 of the assignments and provide confidence in interpreting potential transmission pathways. 423 Fig 4. Phylogenetic analysis of Clade V for taxonomic assignment.Maximum-likelihood 424 phylogenetic tree of Clade V, illustrating the placement of mOTUs detected in environmental 425 samples. Support values (UFBoot and aLRT from 5,000 replicates) demonstrate reliable 426 phylogenetic inference. This clade includes nematodes with varying degrees of public health 427 significance, highlighting the importance of environmental surveillance for both human and 428 zoonotic pathogens. 429 Fig 5. Comparative heatmaps of nematode DNA detection across wastewater treatment 430 plants. Heatmaps illustrate the presence and absence of nematode DNA across all analyzed 431 matrices between 2021 and 2024. Wastewater treatment plants (WWTPs), showing spatial and 432 temporal patterns of detection and identifying facilities that act as persistent reservoirs of 433 nematode genetic material (* indicates samples collected in 2023). 434 Fig 6. Comparative heatmaps of nematode DNA detection across biofertilizers, and food 435 samples. Commercial biofertilizers and food items, evidencing potential parasite transmission 436 routes through the reuse of treated or untreated biosolids in agriculture (* samples from 2023; 437 ** from 2024). 438 .CC-BY 4.0 International licensemade available under a (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 The copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint 19 439 440 Supporting information 441 442 S1 Fig Phylogenetic analysis of Clade IV for taxonomic assignment. Maximum-likelihood 443 phylogenetic tree of Clade I. 444 S2 Fig Comparative heatmaps of nematode DNA detection across wastewater treatment 445 plants. Aguas Claras. 446 S3 Fig Comparative heatmaps of nematode DNA detection across wastewater treatment 447 plants. San Fernando. 448 S4 Fig Comparative heatmaps of nematode DNA detection across wastewater treatment 449 plants. Cañaveralejo 450 S5 Fig Comparative heatmaps of nematode DNA detection across wastewater treatment 451 plants. El Retiro. 452 References 453 1. Koutsovoulos GD. Reconstructing the phylogenetic relationships of nematodes using draft 454 genomes and transcriptomes [dissertation]. Edinburgh: University of Edinburgh; 2015. 455 http://hdl.handle.net/1842/10558 456 2. Smythe AB, Holovachov O, Kocot KM. Improved phylogenomic sampling of free-living 457 nematodes enhances resolution of higher-level nematode phylogeny. BMC Evol Biol. 458 2019;19(1):121. https://doi.org/10.1186/s12862-019-1444-x 459 3. Ahmed M, Roberts NG, Adediran F, Smythe AB, Kocot KM, Holovachov O. Phylogenomic 460 analysis of the phylum Nematoda: conflicts and congruences with morphology, 18S rRNA, 461 and mitogenomes. Front Ecol Evol. 2022;9:769565. 462 https://doi.org/10.3389/fevo.2021.769565 463 4. de Ruiter PC, Neutel AM, Moore JC. Biodiversity in soil ecosystems: the role of energy flow 464 and community stability. Appl Soil Ecol. 1998;10(3):217–28. https://doi.org/10.1016/s0929- 465 1393(98)00121-8 466 5. van Megen H, van den Elsen S, Holterman M, Karssen G, Mooyman P, Bongers T, et al. A 467 phylogenetic tree of nematodes based on about 1200 full-length small subunit ribosomal 468 DNA sequences. Nematology. 2009;11(6):927–50. 469 https://doi.org/10.1163/156854109x456862 .CC-BY 4.0 International licensemade available under a (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 The copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint 20 470 6. Holterman MHM. Phylogenetic relationships within the phylum Nematoda as revealed by 471 ribosomal DNA, and their biological implications [dissertation]. Wageningen: Wageningen 472 University; 2007. https://edepot.wur.nl/121972 473 7. Ministerio de Salud y Protección Social, Universidad de Antioquia. Encuesta Nacional de 474 Parasitismo Intestinal en Población Escolar Colombia, 2012–2014. Medellín: Facultad 475 Nacional de Salud Pública, Universidad de Antioquia; 2015. 476 https://www.minsalud.gov.co/sites/rid/Lists/BibliotecaDigital/RIDE/VS/PP/ET/encuesta- 477 nacional-de-parasitismo-2012-2014.pdf 478 8. Geerts S, Gryseels B. Anthelmintic resistance in human helminths: a review. Trop Med Int 479 Health. 2001;6(11):915–21. https://doi.org/10.1046/j.1365-3156.2001.00774.x 480 9. Matthews JB. Anthelmintic resistance in equine nematodes. Int J Parasitol Drugs Drug 481 Resist. 2014;4(3):310–5. https://doi.org/10.1016/j.ijpddr.2014.10.003 PMID: 25516828 482 10. Vercruysse J, Albonico M, Behnke JM, Kotze AC, Prichard RK, McCarthy JS, et al. Is 483 anthelmintic resistance a concern for the control of human soil-transmitted helminths? Int J 484 Parasitol Drugs Drug Resist. 2011;1(1):14–27. https://doi.org/10.1016/j.ijpddr.2011.09.002 485 PMID: 24533260 486 11. Bogale M, Baniya A, DiGennaro P. Nematode identification techniques and recent 487 advances. Plants. 2020;9(10):1260. https://doi.org/10.3390/plants9101260 PMID: 32992615 488 12. Roeber F, Jex AR, Gasser RB. Next-generation molecular-diagnostic tools for 489 gastrointestinal nematodes of livestock, with an emphasis on small ruminants: a turning 490 point? In: Rollinson D, editor. Advances in Parasitology. Vol 81. London: Academic Press; 491 2013. p. 267–333. https://doi.org/10.1016/B978-0-12-407705-8.00004-5 492 13. Powers T. Nematode molecular diagnostics: from bands to barcodes. Annu Rev 493 Phytopathol. 2004;42:367–83. https://doi.org/10.1146/annurev.phyto.42.040803.140348 494 PMID: 15283671 495 14. Brooker S, Bethony J, Hotez PJ. Human hookworm infection in the 21st century. In: 496 Rollinson D, editor. Advances in Parasitology. Vol 58. London: Academic Press; 2004. p. 497 197–288. https://doi.org/10.1016/S0065-308X(04)58004-1 498 15. Werneck JS, Carniato T, Andrade AG Jr, Tufik S, Andrade SS. Mites in clinical stool 499 specimens: potential misidentification as helminth eggs. Trans R Soc Trop Med Hyg. 500 2007;101(11):1154–6. https://doi.org/10.1016/j.trstmh.2007.07.006 PMID: 17727906 501 16. Cabarcas F, Galvan-Diaz AL, Arias-Agudelo LM, García-Montoya GM, Daza JM, Alzate 502 JF. Cryptosporidium hominis phylogenomic analysis reveals separate lineages with 503 continental segregation. Front Genet. 2021;12:740940. 504 https://doi.org/10.3389/fgene.2021.740940 PMID: 34712264 505 17. Garcia-Montoya GM, Galvan-Diaz AL, Alzate JF. Metataxomics reveals Blastocystis 506 subtypes mixed infections in Colombian children. Infect Genet Evol. 2023;113:105478. 507 https://doi.org/10.1016/j.meegid.2023.105478 PMID: 37406785 .CC-BY 4.0 International licensemade available under a (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 The copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint 21 508 18. Rozo-Montoya N, Bedoya-Urrego K, Alzate JF. Monitoring potentially pathogenic protists 509 in sewage sludge using metataxonomics. Food Waterborne Parasitol. 2023;33:e00210. 510 https://doi.org/10.1016/j.fawpar.2023.e00210 PMID: 37808003 511 19. Bedoya K, Hoyos O, Zurek E, Cabarcas F, Alzate JF. Annual microbial community 512 dynamics in a full-scale anaerobic sludge digester from a wastewater treatment plant in 513 Colombia. Sci Total Environ. 2020;726:138479. 514 https://doi.org/10.1016/j.scitotenv.2020.138479 515 20. Bedoya K, Coltell O, Cabarcas F, Alzate JF. Metagenomic assessment of the microbial 516 community and methanogenic pathways in biosolids from a municipal wastewater treatment 517 plant in Medellín, Colombia. Sci Total Environ. 2019;648:572–81. 518 https://doi.org/10.1016/j.scitotenv.2018.08.119 PMID: 30121535 519 21. Porter TM, Hajibabaei M. Scaling up: a guide to high-throughput genomic approaches for 520 biodiversity analysis. Mol Ecol. 2018;27(2):313–38. https://doi.org/10.1111/mec.14478 521 PMID: 29292539 522 22. Ahmed M, Back MA, Prior T, Karssen G, Lawson R, Adams I, et al. Metabarcoding of soil 523 nematodes: the importance of taxonomic coverage and availability of reference sequences in 524 choosing suitable marker(s). Metabarcoding and Metagenomics. 2019;3:e36408. 525 https://doi.org/10.3897/mbmg.3.36408 526 23. Choi J, Park JS. Comparative analyses of the V4 and V9 regions of 18S rDNA for the extant 527 eukaryotic community using the Illumina platform. Sci Rep. 2020;10(1):6451. 528 https://doi.org/10.1038/s41598-020-63561-z PMID: 32300168 529 24. Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, et al. The SILVA ribosomal 530 RNA gene database project: improved data processing and web-based tools. Nucleic Acids 531 Res. 2013;41(D1):D590–6. https://doi.org/10.1093/nar/gks1219 PMID: 23193283 532 25. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. 533 J Mol Biol. 1990;215(3):403–10. https://doi.org/10.1016/S0022-2836(05)80360-2 PMID: 534 2231712 535 26. Coghlan A, Tyagi R, Cotton JA, Holroyd N, Rosa BA, Tsai IJ, et al. Comparative genomics 536 of the major parasitic worms. Nat Genet. 2019;51(1):163–74. 537 https://doi.org/10.1038/s41588-018-0262-1 PMID: 30397333 538 27. van Sluijs L, Geisen S, Lozano-Torres JL, Sterken MG, Vervoort MTW, Wilbers RHP. 539 Unearthing roundworms: nematodes as determinants of human health. One Health. 540 2025;21:101103. https://doi.org/10.1016/j.onehlt.2025.101103 541 28. Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, Amit I, et al. Full-length 542 transcriptome assembly from RNA-Seq data without a reference genome. Nat Biotechnol. 543 2011;29(7):644–52. https://doi.org/10.1038/nbt.1883 PMID: 21572440 544 29. Seemann T. Barrnap: bacterial ribosomal RNA predictor [software]. GitHub; 2013. 545 https://github.com/tseemann/barrnap .CC-BY 4.0 International licensemade available under a (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 The copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint 22 546 30. Shen W, Le S, Li Y, Hu F. SeqKit: a cross-platform and ultrafast toolkit for FASTA/Q file 547 manipulation. PLoS ONE. 2016;11(10):e0163962. 548 https://doi.org/10.1371/journal.pone.0163962 PMID: 27706213 549 31. KaKatoh K, Standley DM. MAFFT multiple sequence alignment software version 7: 550 improvements in performance and usability. Mol Biol Evol. 2013;30(4):772–80. 551 https://doi.org/10.1093/molbev/mst010 PMID: 23329690 552 32. Larsson A. AliView: a fast and lightweight alignment viewer and editor for large datasets. 553 Bioinformatics. 2014;30(22):3276–8. https://doi.org/10.1093/bioinformatics/btu531 PMID: 554 25095880 555 33. Kück P, Longo GC. FASconCAT-G: extensive functions for multiple sequence alignment 556 preparations concerning phylogenetic studies. Front Zool. 2014;11(1):81. 557 https://doi.org/10.1186/s12983-014-0081-x PMID: 25426157 558 34. Wong T, Ly-Trong N, Ren H, Baños H, Roger A, Susko E, et al. IQ-TREE 3: phylogenomic 559 inference software using complex evolutionary models [preprint]. EcoEvoRxiv; 2025. 560 https://doi.org/10.32942/X2P62N 561 35. Rambaut A. FigTree v1.4.4 [software]. Institute of Evolutionary Biology, University of 562 Edinburgh; 2018. https://tree.bio.ed.ac.uk/software/figtree/ 563 36. QGIS Development Team. QGIS geographic information system [software]. Beaverton: 564 Open Source Geospatial Foundation; 2024. https://qgis.org 565 37. Loukas A, Maizels RM, Hotez PJ. The yin and yang of human soil-transmitted helminth 566 infections. Int J Parasitol. 2021;51(13):1243–53. 567 https://doi.org/10.1016/j.ijpara.2021.11.001 PMID: 34774540 568 38. Lu Q, He ZL, Stoffella PJ. Land application of biosolids in the USA: a review. Appl Environ 569 Soil Sci. 2012;2012:201462. https://doi.org/10.1155/2012/201462 570 39. Bolaños F, Jurado-Zambrano LF, Luna-Tavera RL, Jiménez JM. Abdominal 571 angiostrongyliasis, report of two cases and analysis of published reports from Colombia. 572 Biomedica. 2020;40(2):233–42. https://doi.org/10.7705/biomedica.5043 PMID: 32673453 573 40. Gamarra-Rueda R, García R, Restrepo-Rodas DC, Pérez-García J. First identification of 574 Angiostrongylus spp. in Lissachatina fulica and Cornu aspersum in Antioquia, Colombia. 575 Biomedica. 2024;44(3):416–24. https://doi.org/10.7705/biomedica.7051 576 41. Amorós I, Moreno Y, Reyes M, Moreno-Mesonero L, Alonso JL. Prevalence of 577 Cryptosporidium oocysts and Giardia cysts in raw and treated sewage sludges. Environ 578 Technol. 2016;37(22):2898–904. https://doi.org/10.1080/09593330.2016.1168486 PMID: 579 27080207 580 42. Yakamercan E, Ari A, Aygün A. Land application of municipal sewage sludge: human 581 health risk assessment of heavy metals. J Clean Prod. 2021;319:128568. 582 https://doi.org/10.1016/j.jclepro.2021.128568 583 43. Laura F, Tamara A, Müller A, Hiroshan H, Christina D, Serena C. Selecting sustainable 584 sewage sludge reuse options through a systematic assessment framework: methodology and .CC-BY 4.0 International licensemade available under a (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 The copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint 23 585 case study in Latin America. J Clean Prod. 2020;242:118389. 586 https://doi.org/10.1016/j.jclepro.2019.118389 587 .CC-BY 4.0 International licensemade available under a (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 The copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint .CC-BY 4.0 International licensemade available under a (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 The copyright holder for this preprintthis version posted April 22, 2026. ; https://doi.org/10.64898/2026.04.21.720024doi: bioRxiv preprint .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. 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