water Article Behavioral Parameters of Planarians (Girardia tigrina) as Fast Screening, Integrative and Cumulative Biomarkers of Environmental Contamination: Preliminary Results Ana M. Córdova López 1,2 , Althiéris de Souza Saraiva 3, Carlos Gravato 4,* , Amadeu M. V. M. Soares 1,5 and Renato Almeida Sarmento 1 1 Programa de Pós-Graduação em Produção Vegetal, Campus Universitário de Gurupi, Universidade Federal do Tocantins, Gurupi-Tocantins 77402-970, Brazil; rsarmento@mail.uft.edu.br 2 Estación Experimental Agraria Vista Florida, Dirección de Desarrollo Tecnológico Agrario, Instituto Nacional de Innovación Agraria (INIA), Carretera Chiclayo-Ferreñafe Km. 8, Chiclayo, Lambayeque 14300, Peru; anamariacordovalopez@gmail.com 3 Laboratório de Agroecossistemas e Ecotoxicologia, Instituto Federal de Educação, Ciência e Tecnologia Goiano-Campus Campos Belos, Campos Belos-Goiás 73840-000, Brazil; althieris.saraiva@ifgoiano.edu.br 4 Faculdade de Ciências & CESAM, Universidade de Lisboa, 1749-016 Lisboa, Portugal 5 Departamento de Biologia & CESAM, Campus Universitário de Santiago, Universidade de Aveiro, 3810-193 Aveiro, Portugal; asoares@ua.pt  * Correspondence: cagravato@fc.ul.pt  Citation: López, A.M.C.; Saraiva, Abstract: The present study aims to use behavioral responses of the freshwater planarian Girardia A.d.S.; Gravato, C.; Soares, A.M.V.M.; tigrina to assess the impact of anthropogenic activities on the aquatic ecosystem of the watershed Sarmento, R.A. Behavioral Araguaia-Tocantins (Tocantins, Brazil). Behavioral responses are integrative and cumulative tools that Parameters of Planarians (Girardia reflect changes in energy allocation in organisms. Thus, feeding rate and locomotion velocity (pLMV) tigrina) as Fast Screening, Integrative were determined to assess the effects induced by the laboratory exposure of adult planarians to water and Cumulative Biomarkers of samples collected in the region of Tocantins-Araguaia, identifying the sampling points affected by Environmental Contamination: contaminants. Furthermore, physicochemical and microbiological parameters, as well as the presence Preliminary Results. Water 2021, 13, of inorganic compounds (dissolved aluminum, total barium, total chloride, dissolved iron, total 1077. https://doi.org/10.3390/ fluoride, total manganese, nitrates, nitric nitrogen, total sulfate, total zinc) and surfactants, were w13081077 determined on each specific sampling point. The behavioral biomarkers (feeding rate and pLMV) Academic Editor: Heiko of the freshwater planarians were significantly decreased when organisms were exposed to water L. Schoenfuss samples from four municipalities (Formoso do Araguaia, Lagoa da Confusão, Gurupi and Porto Nacional), sites of the Tocantins-Araguaia hydrographic region—TAHR. Both behavioral biomarkers Received: 20 February 2021 decreased up to ~37–39% compared to organisms in ASTM medium only. Our results showed that Accepted: 11 April 2021 these behavioral biomarkers can be used for fast screening monitoring of environmental samples of Published: 14 April 2021 freshwater ecosystems, since a decrease in feeding rate and locomotor activity was observed in sites impacted by anthropogenic activities. However, the absence of effects observed in some sampling Publisher’s Note: MDPI stays neutral points does not represent the absence of contamination, since several other classes of contaminants with regard to jurisdictional claims in were not determined. In these negative results, the absence of deleterious effects on behavioral published maps and institutional affil- biomarkers might only be indicative that the potential presence of contaminants on such sites does iations. not significantly affect the performance of planarians. This fast screening approach seems to be useful to determine contaminated sites in freshwater ecosystems for biomonitoring purposes. This knowledge will help to develop biomonitoring programs and to decide appropriate sampling sites and analysis. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. Keywords: biomonitoring; planarians; locomotion; feeding rate This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). Water 2021, 13, 1077. https://doi.org/10.3390/w13081077 https://www.mdpi.com/journal/water Water 2021, 13, 1077 2 of 13 1. Introduction Tocantins state (Brazil) is consolidated as the new agricultural frontier of the country, strategically located by environmental conditions and available water resources. In the last few years, Tocantins state has been standing out in the scenario of the national agribusiness of grain production [1], sugar cane [2], melon [3], and watermelon [4]. The increase in agri- cultural production has facilitated the spread of diseases, pests, and weeds in crops [5,6]. Thus, for achieving high productivity, pesticides and fertilizers have been adopted as the most efficient manner for the short-term control of undesirable organisms [7,8] and have been used in various steps of the production cycle of cultures, whereas such compounds be- come subject to environmental contamination [9,10]. However, the use of these compounds in agriculture is not unanimous, although its impacts can be considered positive by some segments of society; for others, its impacts are negative, mainly through the environmental point of view [11,12]. In the Tocantins state, agricultural cultivation generally occurs in areas adjacent to aquatic systems (watershed Araguaia-Tocantins). Thus, the aquatic ecosystem can be impacted since the main routes of contamination by xenobiotics, such as metals, in aquatic systems are through runoff, erosion, drift, leaching, and atmospheric deposition [13,14]. Thus, water quality has been influenced by urbanization and modernization, which has brought problems of wastewater disposal and the contamination of surface water, such as lakes [15]. Natural water becomes polluted due to the weathering of rocks, the leaching of soils, and mining processing [16]. The change in land use in agricultural production could increase the use of fertilizers with subsequent leaching to waterways, rivers, and lakes, increasing the risk of eutrophication and the loss of biodiversity [17,18]. Fertilizers have a significant amount of arsenic, chromium, cadmium, lead, zinc, nickel, iron, molybdenum and manganese, which are essential in the healthy growth and maintenance of plants. However, the excess of these metals in sediments of freshwater produces toxic effects to aquatic organisms [19,20]. Heavy metals enter the human body mainly through ingestion, through food, inhalation and dermal contact, such as emissions of waste material in the form of smoke, dust particles, and substance vapors of chemicals from various industrial activities, such as mining and agricultural practices [21]. Exposure to heavy metals can cause their excessive accumulation in body tissues and induce the production of free radicals (reactive oxygen species (ROS) and reactive nitrogen species (RNS)) that lead to an oxidative stress condition. Elevated levels of Zn and Cu can cause various adverse health effects; otherwise, these elements are essential for life and functions of many proteins in the organism. Among the measured elements, arsenic, cadmium, chromium (VI) and nickel are classified as carcinogens [22,23] by the International Agency for Research on Cancer (https://monographs.iarc.who.int/list-of- classifications, accessed on 7 April 2021). Copper is not classified as carcinogenic and there is only one publication on Cu as a tumor promoter [24], cited by Taylor et al. (2019) [25]. Water quality can be assessed by various parameters, such as biochemical oxygen demand (BOD), temperature, conductivity and concentrations of nitrate, phosphorus, potassium and dissolved oxygen. Among many other classes of contaminants, heavy metals are usually of special concern because they might cause poisoning in aquatic animals [15]. At the level of the trophic chain, the most sensitive organisms are those most affected, and in fact, contamination of the aquatic ecosystem, whether due to bioaccumulation or direct exposure, will ultimately lead to the exposure of humans [21,26]. Thus, contamination of aquatic ecosystems has been monitored by analyzing the effects of the presence of contaminants using bioindicator species, which reflects the health state of that specific environment [27,28]. The use of organisms as bioindicators for the evaluation of environmental contam- ination has been used in several studies, since this strategy offers various advantages concerning the prediction of the flow of contaminants in the populations of the trophic chain [29,30]. Planarians have gained more and more notoriety in ecotoxicology as test organisms with potential for biomonitoring contaminants in freshwater ecosystems, mainly Water 2021, 13, 1077 3 of 13 due to: (i) a useful potential to screen contaminant toxicity and assess the quality of fresh- water ecosystems; (ii) several interesting biological characteristics (for example, behavior, regeneration, and reproduction) that can be used to evaluate the sub-lethal and chronic toxicity of environmental contaminants; (iii) some physiological systems that share resem- blances to those in mammals (e.g., the nervous system); (iv) being a representative group of invertebrates with wide geographical distribution, functioning as prey and predators; (v) ease of capture and low laboratory maintenance costs [31–34]. Among the freshwater planarians used as test organisms in ecotoxicological bioassays, Girardia tigrina (Paludi- cola, Dugesiidae; Girard, 1850) has been used to evaluate lethal and sub-lethal toxicity of xenobiotics and potential biomonitoring [35–37]. Behavioral biomarkers, such as feeding rate and locomotor activity, have been de- veloped as low-cost tools, but with high sensitivity and acceptance as integrative and cumulative responses induced by xenobiotics that are indicative of deleterious cellular alterations and effects at higher levels of biological organization [37]. Moreover, although scarce, the effects of metals on freshwater planarians have been reported in the literature, such as copper’s effects on antioxidant defenses in Dugesia japonica [38], the genotoxic effects of copper in Girardia schubarti [39], and aluminum’s neurotoxic effects in Dugesia estrusca [40]. Additionally, although not a metal, the effects of chlorine have been reported on the feeding, locomotion, regeneration and reproduction of Girardia tigrina [28]. Thus, our present study aimed to determine the usefulness of such biomarkers to assess the environmental contamination of water samples coming from the watershed of Araguaia-Tocantins through the laboratory exposure of adult planarians. These wa- ter samples were collected in areas of intense agricultural production and exploitation of mineral resources. In addition, this study also aims to gather information about the behavioral biomarkers and its potential use as fast screening tools that can be adopted to determine important decisions concerning further biomonitoring studies complemented with chemical analysis of different freshwater compartments. 2. Material and Methods 2.1. Study Area Water samples were collected in four municipalities, Formoso do Araguaia (11◦48′02.8′′ S and 49◦37′26.3′′ W), Lagoa da Confusão (10◦50′64.3′′ S and 49◦42′51.0′′ W), Gurupi (11◦51′33.96′′ S and 48◦53′15.14′′ W) and Porto Nacional (10◦47′41.83′′ S and 49◦37′22.854′′ W), of Tocantins-Araguaia Hydrographic region (TAHR). Those sampling sites represent areas of intense agricultural production and exploitation of mineral resources (Figure 1). More- over, a local reference site for water sampling was chosen considering a location far from nearby sources of human impact and therefore less contaminated (Figure 1). The sampling period was conducted during the wet season, i.e., January to February. 2.2. Water Analysis The sampling, storage and transport of the water samples to the laboratory were carried out following the specifications of the sampling of surface waters according to the National Water Agency [41]. Then, samples were subsequently sent to the Conagua Ambiental laboratory for analysis (Goiás State, Brazil—https://conaguaambiental.com.br/ wp/, accessed on 15 July 2020) and also used in the laboratory for exposure of planarians. For the analysis of the water samples, they were collected in borosilicate glass bottles and PET containers for the first use, containing the necessary preservatives (Conagua Ambiental protocols—https://conaguaambiental.com.br/wp/, accessed on 15 July 2020) to avoid the deterioration of the sample. The collection was carried out at a depth no greater than 30 cm. Later, the flasks were sealed and transported to the laboratory at a temperature of 4 ◦C. The water samples for the exposures were collected and transferred at 4 ◦C and expected until the sample reached the temperature for conducting the experimental tests, 22 ± 1 ◦C, without the addition of additives. Water 2021, 13, 1077 4 of 13 Water 2021, 13, x FOR PEER REVIEW 4 of 14 Water 2021, 13, x FOR PEER REVIEW Analyses were carried out on the water samples to determine chemical, phys4i coafl 1a4n d biological parameters following the methods of the Environmental Protection Agency and Standard Methods for the Examination of Water and Wastewater [42]. Figure 1. Map of Tocantins-Araguaia hydrographic region (TAHR), Brazil. (A) Formoso do Araguaia, 4 (Taboca), 5 (small irrigationF cihgFuaignreun re1el.) 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Water c=o Wlleactteior ncoslilteecst.ioWna stietresc.o Wlleactterd cionlleacctehds itne ewacahs usisted wtaose uxspeods etoa edxupltopsela andaurilat ns pla(Gna. rtiagnrisn a(G) i. ntitghreinlaa)b ionr tahtoer lya.boratory. 2.2. 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T3h0T ech mwe.ap Ltleaarnt esarar,mi athnpesle fhsla afvsokers tt hhweeei rreexe pasteoianslugerdbe sea hnwadev ritoera rcnaosllptleeorcrettdeeda catcnoo dtrh dterina lngasbtfooertarhteeodrc yah tea m4t a°icC tae lmcopmerpao-si- and expteucrtteiod on uf on4f t°itlCh te.h Tweh saeat emwrapintletr hr seeamnchapteulder sat hfloeer nt tevhmierop enexrmpaoteusnurter[ e4fso4 r]w. cDeorenesd pcuoictlelteintchtgei sdt,h waen eedxd ptirdearnnimsoftendrrteeatdle r amt i4n e°Cth e tests, 22 a±n 1hd a° eCrxd,p wweciattheeodru iunt ntththiele tadhdiefd fseitarimeonnpt olwef araetdeadrcihstaeivmde psth.l ees tsetmudpieerda.tuInret hfoisr wcoany,dwucetuinsge dthAeS eTxMpehriamrdenwtaalt er Anatelysatssse,sa 2 wc2o e±nr t1er o°cClatr,rr weieaidttmh ooeuunttt o ,tsnhi ent hcaeed twdhiaetitpoelnra snoaafm raipdanldeicstu itvolte udsr.e eteisrmmianien tcahinemedicinalt, hpihsycsuilctaulr eanmde dium and biological pwaerAawnmeaerleytesaresbs lf ewolteloorewd ceiantergrr mitehdien omeutetht hoenond uthsm eo bfw etharteoe Efr nssaavlmitrsop(nlsemosd etionu tdmael thPeyrodmtreioncgteie ocnnhc eAamrgbieconancl,ay pt aehn,ymds iacganl easnidu m Standardb iMosluoeltgfhaioctaed,ls pp foaortraa tsmhsieu tEemrxsac fmholliolnoraiwdtieion,nga on thfd eWc maaltceeiturh moandsdsu oWlff atahtseet)e Eawnvavatiielrarob n[l4me2t]eo.n tthale Porrogtaenctisiomns A. Fgoernecyxa amndp le, Stacnadlcaiurdm Mioenths oindsth feora qthuea tEicxaemnviniraotniomne onft Wareatceorn asnidde Wredasttoewbeatienrd [i4sp2]e.n sable for the feeding 2.3. Planaribaenhs avior of planarians, and exposure to higher levels of calcium ions enhanced the feeding 2.3b. ePhlaanvaiorira,nssh owing that there was a good correlation between the concentration of calciumThe spioencsimanendst hoef Gre.s tpigorninsiav uenseedss ionf tphlea nbaioriaasnssaytos wfoeordes o[4b4ta].inIneda dfrdoimtio tnh,et hUenaimveorusintyt of calcium of Sao Paulsoa laTtnhcdae nmspbaeeicnuitmpaientnoesdfi o fitfny G lta.i bmtiogerrsainttohar euyas cemudlo tiuunrn tethso eif nbp itoohateas Fssseaidyusem rwasle aUrletn owivbiettarhsionitueytd ou fnr Tofaomvc aotnhrateib nUlsen, rievseursltistyf or Tocantinosf Staaot eP-aBurlaoz ialn, dsi nmcaei n2t0a1i4n.e Ad mine lraibcaonra Stotaryn dcaurldtu rTeess itn a tnhde FMeadteerraial lUs n(iAvSeTrsMity) ohfa rTdo cantins, water wTaos cuasnetdin sa sS ata tceu-lBturarzinilg, sminecdei u2m01 4[.4 3A].m Oerigcaani sSmtasn wdaerde Tmeasitn atanidn eMd aitne rcioanlst r(oAllSeTdM ) hard conditiownsa tienr p wlaasst icu sbeodx eass (a3 0c u× l1tu8r ×in 1g0 mcmed3)i,u cmon [t4a3in].i nOgr g1a Ln iosmf As SwTeMre m meadiinutmai,n aetd 2 i2n ±c 1o ntrolled conditions in plastic boxes (30 × 18 × 10 cm3), containing 1 L of ASTM medium, at 22 ± 1 Water 2021, 13, 1077 5 of 13 planarians [45]. On the other hand, in the collection of water samples in the field, it was not possible for us to determine an uncontaminated reference point to adopt as a control (in addition to the control with ASTM medium). Individual G. tigrina (0.83± 0.11 cm in total length) were exposed (n = 10 per condition) during 96 h to 20 mL of 12 water samples, on Petri dishes (Ø = 4.6 cm), including the reference site (Figure 1) and a laboratory control with ASTM water only. The exposed organisms were maintained at 22 ◦C ± 1 under dark conditions and no food was provided. After four days exposure, planarians from each condition were transferred to clean medium and locomotor velocity and feeding rate were determined as post-exposure analysis. Briefly, planarians were individually transferred (n = 10 per condition) to new crystal- lizing dishes containing 20 mL of ASTM medium, and twenty live larvae of Chironomus xanthus (six days old) were released on each plate. Then, the feeding rate per hour was calculated, analyzing the number of larvae consumed per planarian at the end of 12 h. To determine the locomotor velocity (pLMV), planarians were placed in a plate (Ø 35 cm) with 200 mL of ASTM hard water and an adhered millimeter paper (grid lines spaced 0.1 cm apart) below. The pLMV was measured individually, after scoring the number of crossed grid lines for each planarian for 2 min (taking as reference the crossing of the planarian head) according to the methodology already adopted by our research group [28,35,36]. There was no mortality of planarians during the experimental assay. 2.4. Statistical Analysis For pLMV and feeding rate data, we used one-way analysis of variance (ANOVA) followed by Tukey’s post hoc test for multiple comparisons in order to determine differ- ences between sampling and reference sites and the laboratory control. Prior to ANOVA, the homogeneity of variances of data was assessed using the Brown–Forsythe test and the normality of data by using the D’Agostino and Pearson test. Locomotion data were transformed (Y = rank(Y)) for the correction of homogeneity of variance. Statistical analysis was performed using the software GraphPad Prism version 7.0 for Windows (GraphPad Software, La Jolla, San Diego, CA, USA). 3. Results 3.1. Sampling Sites Disturbing concentrations of aluminum were found in the surface water samples at points 2, 3, 7, 10 and 11—at these points, concentrations of 0.10, 0.13, 1.02, 0.27 and 0.38 mg L−1 of aluminum were detected, respectively (Table 1—concentrations higher up to 10 times the limit acceptable). For these points already indicated, the pH was variable, obtaining values of 5.44, 7.1, 7.25, and 6.97, respectively. The water sample collected at site 1 (Lagoa da Confusão lake) affected the planarian locomotion, decreasing to 36.18%; in this sample, concentrations below the acceptable limit of inorganic compounds (total fluoride, total manganese, nitrates, nitric nitrogen) were found (Table 1). The water sample collected at site 2 (water channel, Lagoa da Confusão) altered the pLMV of the planarian, decreasing when compared to the control. In this sample, concentrations above the permissible limit of inorganic compounds (dissolved aluminum, dissolved iron) were found (Table 1), as well as an acid pH of 5.44, affected the feeding rate and pLMV of the planarian. 3.2. Feeding Rate Planarians exposed in the laboratory to water samples from the Tocantins Araguaia hydrographic region caused the alteration of their post-exposure feeding rate. Significant differences were found in sampling sites when compared with the ASTM condition in the laboratory (p < 0.0001, Figure 2). Planarians, when exposed to water samples from site 3 (Urubu river—Lagoa da Confusão), site 8 (large volumes of water in the channel—Porto Nacional), site 2 (water channel—Lagoa da Confusão), site 6 (large volumes of water in the channel—Formoso do Araguaia), and site 9 (small irrigation channel—Porto Nacional), Water 2021, 13, x FOR PEER REVIEW 6 of 14 Wat er 20W21a,t e1r3 2, 0xW2 F1Oa, t1Re3r ,P2 xE0W 2EFa1ORt,e R1r3 E2P, 0VEx2EW IF1ER,OaW 1tRe3 rE , P2xVE0 IFE2O1RW,R R1 3PE,E VxEI FEROW RRE PVEIEWR REVIEW 6 of 14 6 of 14 6 of 146 of 14 6 of 14 TheT whea tweraT steharme swpaTmlaeht pecerlo e wls laceaomcTtltehlpereed lcse twaa ecmtdao st plaielteltre 1 (Lagoa dloTcohme owtaiotenr, sdaemcrpelaes cinogll tcoted at site 1 e( c L stciaetomedgl l o1ape atcl( eLtsde iacadtgoe C oal1l atae ( csCdLitteoaed gn C1 ofa uoa(tnLs sdãonfusão lfaiu oatgke s oCl ãae1a k )o (d n e aLl ) ffafau k aegCcse foãft)o e e aona c d dfl tfaueaekds cCãe tto)eoh d anleaf ftpkuhelecsa)tã nar th p nar epioadlf nalf aten i h akcantere )ipd aaln aftf hneeac rtpeialdan nt haeri apnla narian locolimmoliott icooofnm i, nodlotoeircogornaem,n aldiosocite cniccogronme m,ta ospdlt ioioen3ocu6gnor e3,mt a6.n1d8odo%s . 1eit3n8%s (c;i6 otrgoi.en1 a ;t,8 inta ost%ldih nfe3; il gsc6 t ui hr .n1eti os osr8atim %sh s3iian;6s mg. ple, concentrations below the acceptable dep,li1ens 8,at o%mtch o;3pi ns6il cne.s1e, a 8ntcmh%torispna; tclisienoa,n mtctshrop ainbsltec io,sel aoncmwsotr n pabtctlehieloen,o n twcarsoac nbctihceoeplnon tswat rcbb acltethil poetn waasbc tlbcehe epl otawacbc lethp et aabclcee ptable limwit eorlfei m ifnoiotu rongfldai m in(nTiiocta rbcogloilfame ni 1niptc)o . orcTugfolh aniimend piowsict or (agcouttaofne nmtrdiai nscslp oa of(crmltuogopmnaotandlrpelis d coc f e(luocut,lno oltmtedrasi lpd t(fooetltal manganese, nitrates, nitric nitrogen) octtaeld ,uom atnoaotdr ltnis asdfig tle( auetm, no 2tetaro a(isntdwlea ge,fl al ,n umntioetarstnaiedtgl, eanms,n ,i taenornsaitegatr,eal i scnm, ietnasriieant,trg eoinacsgin ,te nerniasti)ter er,o signc, eintnri)at rtioecsg ,ne niti)rt origce n)it rogen) werfue sfãowoue)n raedl tf(eoTwruaeenbdrdl eet h (fw1Toe)ua .e pbnrTLeldhe Mf e(o1 TVw)u.a neaTbordthlfe e (rt fTh1 ows)au.b anTltedh r e1( sT)w.a aTmabhtlperl e1 ws )ac.a omTtlehlpree lcse twa ecm ater channel, Lagoa da Con- e mplpalnea croialne,c dteedc raeta ssiitndaoegt plae2l eltr we( c w sthciaetoaemedlnt l e2ape r ctcl( oetwcse mhicdataoept n ael2alnrter (ecsewitlhdt,e ea dLt nt2oa ean g r(tte wo hcslah,iea t La tdecena ao2rgn n Cco(etwhlaor,ao nadLnlt-.aen gIreCn olc o,ah nL ad-anagn oCealo, dnL-aa gCooan d- a Con- fustãhoi)s f auslsatãemore) dfau lttsheãeroe p)df Lua tMslhtãeeVorthis spamtleh,pi scl eos,na tchmcoeispnn lctser )e pa odaLtffiu lMo ttshenhãVresoe dp)oap L bfalt MalohttnhveVaer eper poiLdtahlfM na tethn, hV eapde ree opiprcafLmr lnMateh,ina sedVsas ier pniocalgrfane ntwa,h asdherien iapcngnrl ae,wc naodshameirencipnarge an cawr,o esdmhine pgctnor a we rctaeohsdmei n tpcgo oac nrwtohetmhrdeoe pcltn.ao rI ncnetothd rmeo tlpco. oa Itnrhet erd o clt.o nI nthr oel .c oI n trol. In thiss oslavmedp lael,u cmoinncuemnt,r adtiiesoa,sn mtocthsrolp vainsaltee cbido,seo a ncvimsortero n pantctlbh)ie oen,w nv tcprseeoa ernaterihcb moeonni vsptse rei abrtbtmhlieo ieb vin s l lepis e m i e btalrhlibmmite o oivl ipsfi tsem i orbtimfthl inorno eeiro sg lfspi aimibenn grlioeamt nroligiisfcams nicbinitoclo em or cgflpo iamionuiopctnr o dgocusafon nmi(dindcspoi sorc(-c comp unds (dis- gduoaminsnd-pisco u(cdnoimds-sp o(duins-ds (dis- solvafefdes coatelvudem tdhi sneaou lflumvemee,dd isdin onaiulsglvmus eorma,dl vtd iesneai odlusaulsn vomiderl,ovd ipnde Luai)ds Mlm wsuiorVm,e lovdr inonei)f sdu fstw mhoiurlee, fvor oednud )ifns owsidruo oeln(vrnTde)a dfb(woT lieuear robn1enld) e,)f o(a1wTus)a, en wbradelseln pl a(nTaarbialen .1 ), as ll ea ( fswT lo1 a) aue,bsl nla l deasan cs1(w i T) ac da,ea nlab id pl s laHea cw ps i1 od Hea)f ,ln of pl5 a Ha.s4s c 5 4 wioa .4 ,d fen 4lp5 l,a . H4ac4is do, a fpn 5H .a4 c4oi,df 5p.4H4 ,o f 5.44, affecteadf ftehcet efdeaef tfdheicent gfeaed fref adtethcienet ea gfdne ar edfatfdh tepeicLn tafgMend erdVd at tphioenLef ga Mft nehrVadetd epoi Lnflaa gMtnnh draVea r p tioLealf nMa t.nh Vader oipafLln atM.hn eaV rp ioalafn nt. haeri apnla. narian. Table 1. Analysis of surface water samples collected at eleven sampling sites (1–11) and the reference (12) site in Tocantins. Table 1T. aAbnlael 1y.Ts Aiasb nolafe lsy 1uTs.r aiAsfba onlcefae sl 1wyu.T srAaifatsaneb ocralef les yswa 1usm.air sAtfp eaonlrcfe ae sl a uwycmrosafilpatsle clorce fst s we sacdumoa rlatflpetear lece stlesea wvdcmoe aplntlle sercasl tes mecvadompel nalpeit ns cleaegtlemse sd vcip toeaelnltisl n es(gcl1aet –msev1idetp1en a)lsi tsa n( aen1gml–d es1 vpit1thele)ine sna rs(gne1a dsf–mei 1trphe1es)elni a(nrc1neg–fd (1es1 ri1tt2he)e) neas s c nr(ie1td ef–( e t1ihrn21e) )Tn sraocientecfed ea( ir1n nte2ht ni)Ten cso sreic.et (eaf1e ni2rnt)ei Tnsisoct.ec a(i1n2t Ti)n ossic.ta en itnin Tso. cantins. Site Water 2021, 13, 1077 Sites oS si tof Hf Heys dorSf y o diHgt rery o asd g poSr r hfo ai it pgHerhc syRa i dpoc efrhS R g oiHi egcot geyrnRas ido e Tpor nghofi gci ToHcarn o anRy cptTde a ihrnog noicitscog ia nRnras teT pignhoisoci can nR Tteiongcsiao n t iTnos c antin s TesTt est Test ATLes At L TLeAsQtL Q ALUL QniU tA Araguaia 6 of 13 Test AL LQ Unit nLitQ UnLitQ U nit AUrnaigt uAairaa guaAiara guAaira guaAiar aguaia 1 1 2 2 13 3 214 5 6 7 1 2 3 4 54 32 1 65 43 2 76 54 3 87 8 65 4 98 76 9 5 109 87 1 06 1110 98 1 17 112190 1 8 2 1211 0 9 1211 0 121 1 12 BiocBhioecmhicalBiochemi ale omBxiio coxygen ygcahel enoBm xioyicghaelen moB x5iyoc agclhe onemx yigc0ae.2ln o xygen −1demand 5 mg L 5 0.2 5 0.2m g5 L0−.12m g5 L0 s.−h2 1 mo wg eL0d − . 1m2a gs i gL n i fi m cga nL t − l 1 y d − 1 e c r e a s e d f e e d i n g a cdemand demand t iv i t y o f 3 8 , 3 4 , 2 8 , 2 6 a nd 2 5 %, r e s pe ct iv ely, deman deman Didsesmolvanedd oxygen >5 0.1 mg L−1 when com p ared to t4h.7e AS3T.9M co n trol c o ndit i on (F i gure 2).DissolvDeids sooxlDyvgeisdesn o lxvyDegdies >osn5ox lyvgeedn> o 50x .y1g e>n5 0.1m g> 5L0 .1 mg L0 .m1 g L m g L − 1 4.7 3 .49. 7 3 4. .97 3 .49 . 7 3 .9 2 . 8 2.8 Dissolved xygen >5 0.1 mg L−1 − 1 − 1 − 1 4.7 3.9 2 . 8 2. 8 2 .8 TurTbuidribtiyd Tituyr bidTiut1yr0b 0i1 d0iTt0yu r0b.i12d01i0 t. 2 1 1000N .2T1UN 1 T000U.2 1 N T 0U. 2 1N T U N T U 2.8 ATcuidrb Ai idity ctiyd/iatlykA/aaclliikdnaiittlAyiyn/ 10 caiitldyk6 0.0 T–abli atyliA/6na9.cil0.tki0y–d e 1.2. 1A0 n.1a lysisNoTf Usu rface wa ter sa mples collec t ed at e leven saa9 ilt.i0yn6 /ia.t0ylk– 9a0.l.0i16n .0it–y9 0.p0.1 H6 . p0–H09 .10 p H 0 .51 . 4p45H .4 4 p5H .4 4 5 . 4 4 5 m p l ing . 44 si t es (1– 1 1) an d the r e feren ce (12) site in Tocantins. Acidity/alkalinity 6.0–9.0 0.1 pH 5.44 Total dissolved Total dTiostsaoll vdeiTsdos otalvl eddis solved Sites of Hydrographic Region Tocantins AraguaiaTotal dTiosstaol vdeidss olved 500 Test 0.05 mAg LL−1 LQsolids 500 500 .s0o5l i5d0s0 . 05m5 g00 0L . −01m5 5g0 0L0.0 − 15 m g 0L .− 0 1m 5 g UL n i t − 1 m g L− 1 solids solids 1 2 3 4 5 6 7 8 9 10 11 Cysoalnid solids 12 osb acterial Biochemical oxygen CyanoCbaycatneoribCaaly catenroiCabyla ac5nt0eo,r0biC0aad0lyce tmaenarnoiadbl1a cterial 5 −1 0.2 mg L −1 density 50,000 50, 0010 5 0,C00e0l1C m 5e0Ll ,m0 01L0C e l m LC1 e l mL C e l m L − de densityd e5n0s,i0tdyD0e 0isn ssoilvtyed 1eonxysgiteyn Cel mL −1 >5 −1 0 .1 −1 mg L −1 −1 1 4 . 7 3. 9 2.8 Dissolvnesidty a luminum 0.1 0.004 mg L−1 DissolvDeidss aoluvDmeidsi nsaoululDmvmei sdisn oau0l.vmu1Dem disi nTas0uoluu.rl01bvm. i0ed i0dint4y ua 0lm0.u1.m0 0mi4n0 gu.10 mL .10− 010m 04 g00. 1L.0 −0 10 4m .2 1g 0 L.0 0m0 .41−1 g 10N L.T10−U1 . 11 m 30 g.01 .L31 − 1 1 0 .. 13 1 0 1.02 0.27 0.38 Total barium A0ci.d7i ty/alk0a.l0in0i5ty m6.0g– 9L.0 0.1 0 .11 0 .p1H3 5. 44 . 01 .31 .10 2 0 . 113. 0 2 1 . 0 2 0 . 21 7. 0 20 0. 3.287 1 . 0020. 3. 28 7 0 ..32 87 0.03 .8 2 7 0 . 38 −1 Total bTaortiualm b Taroituaml bT 0aoT.rot7iatu allm bda iT0srs.o0i7out. la0vml0e d5b 0sao0.r7l.u0 0m50 .70 .0 m5 g00. 7L.0 0 5m g0 L.0 m0 5g L − m 1 g L − 1 ids 5−010 −10.05 −1 mg L−1 TotTalo chloride 250 0.5 gm L −1tal chTlootraild cTeh oltoarlCi dcyheaT2n lo5o0tbrai adlc teceh r2ila5ol0r .i5d e2 50 g.5 mL 2g5 L0. 5 mg L0 .m5 g L m g L − 1 Total chloride −1 −1 −1 −1 −1 TotTalo ctahll ocri ne 2500 .01 0.5 mg 5L0,0 00 1 Cel m L density −1 Total chlorinehT lootrailn cTeh0 o.lD0toai1rsl is ncohleT0v le.o0dt0r1aai nl e 0c h0.01 .l0u1mi.ln0o0u1r.m0 in1m0e . 0 m10 .g0 mL 0g.0 L1.0 1 m g 0L. 0m 1 g L m g 0L . −0 1 4 0 .04 0 .0 4 0 . 0 4 0 . 0 4 0 .0g L0−1.1 − 10. 004 − 1 mg L− 1−10.04 0.11 0.1 3 0.07 7 10. 0. 02 7 0 . 0 7 0 .0 7 0 . 07 Dissolved iron 0.3 −1 0.27 0.38 DissolvDeidss iorlovDne ids siorolDvnei0 sd.s3 oi rlTovoDnet0ad i.ls3 0bis ra.o0orli 0.04 4nvu m e0d.03 . i0ro4n 0 .3m0 .0g0. m74L g0. 03L. 004 m. 00g 5 0L. 00m 4.3 gm60 gL.3L06 −.34 mg L−1 − 1 0.3−61 0.34−1 m 1 0g. 03 .L43 − 61 0 .. 34 6 0 . 03 .403 .6 0.6 2 0 . 3 204 . 6 2 0 . 6 2 0 . 0 80 8. 6 .88 2 0 . 8 8 0 . 6 20 .8 8 0 .8 8 0 . 88 TotTalo fluoridTotal fluotarild felTu o etra ild feTl uo1.ot4ar 1 liT d .fo4letuT a1 lo.4crt0h ai 0 .dl0lo e4rfi −1 −1 Total chloril .d nu1 0e.4eo04 r. i0d4e 1 .4mmg 0L 2. g05 0L −10.0m4 1 g1. 04L. 04 m 0 .5g 0L. 0m 4 gm gL L − 1 − 1 −0.01 mg L 1 − m 1 g L − 1 0 .0 4 0 TotTalo mtaal nmTgaanese 0.1 −1 .07 Total manganeosnteag la mnTeoastn0ea.g l1 am DnTaiesons0toeg.al01 val nme 0as.0en00 0.g17.a0 n0e70s e.1m0 .g L−10m7 g00. 1L.0 −01 7m g 0 L.0− 1m0 7 g L m −1−1 g L − 1 NitrNaittes 10 .e0d0i70r o.1n mgmL0g. 3 L 0 .04 −1 m g L rateNs itratNesi Ttroata1tle0flsN u oi 0. 36 0 .3 4 0 .6 2 0.88 NNiittrriact nesit rogen 10 1 0.1 tr rida1et0e0 s. 1 10 01−.1.1m4 g1 0L0 .−110 m.04g L0− .1m1 gm gL L−1 − m 1 g L − 1 Total mang Nitric nNitirtorigce Nni troicg neNnit ir1to rgice0 mg L − −1 1 Nitric nitrogen 1 Ni0tr.a0t0e an.n0es1 it 0se10r1 o.0 g0e1n 1 m 0.1 0.007 0 .0g0 mL1 g01 L. 00 1m g 0 L.0 m0 1 gm gL L m g L − 1 −1 − Total sulfate mg L10 1 − 1 − 10.1 mg L−1 −1 Total sTuolftatle s uTloftaatle sT2uo5lt0fa 2 Nl 5t e0s u2 itrTic5lof0nat ael0 s.21u51l0f .a 1t1e2 5m00 .g L i.t1ro1g en mg L−11m1 2g5 0L0.1 − 101 m. 00g1 0L .− 1 1m 1 gm gL L− 1 − m 1 g L − 1 TotTalo ztainc −1 −1 Total zinc l zWTinoactte al 0 r 02 zT.01i2on81tc .a1T l8o 0zt a, 13,. i1T l0n8s 0.00 x .o ulfate Fc0 O t0a7Rl0 z.P01i 7 En.80E c0 70 .1 m mg0 8L. 20 g5 L−10 R REVI0Em 7W0 g.01 L.80 00 7m.1 1g 0 L. −1 0 − 1m0 7gm gL L− 1 − m g L − 1 0.44 Surfactants NR 0.001 mg L 0.74 0.6 1 0.4 4 0 . 4 4 0 .4 4 0 . 4 4 0 . 44 Total zinc 0.18 −1 0.007 mg L 0.44 7 of 14 SurfacStaunrtfsa ctSa unrtfsa cNStauRnr ftasS cuNtraSf0Rnauc.t 0rtsaf0 an1tcNs ta0Rn.0 t0sm1 N gR0 L. N0−10Rm 1N g0 RL0.0. −7010 41m.0 0g100 .L6..07−11m04 1 gm0 10 0.gL6.068L−.17 . 6 4m8 0 g 0.76 0.64 0.63 0.64 0.62 0.7 0.61 0.59 96 h) and a shorter post-period of feeding (<12 h) would better reflect the increased energy required for maintenance and defense mechanisms [53]. Although in our study planarians have been exposed to TAHR water samples for 4 days (96 h static exposure), there still seems to be no consensus on the specific number of days planarians should be exposed in static or semi-static conditions—usually from 8 days of exposure up to 14 days [35–37]. Feeding tests reported in the most recent scientific literature generally occur for a period of 3 h, when organisms are exposed to a specific contaminant [35–37]. According to our results, it seems that the feeding activity of planarians is dependent on the locomotor activity and feeding requirement of exposed planarians: (i) planarians exposed to water of less contaminated sites showed a decreased locomotor activity and probably a low requirement of food; (ii) planarians exposed to highly contaminated water also showed a decreased locomotor activity, but an increased requirement for food to deal with deleterious effects of contaminants. Therefore, those differences seem to be more evident in feeding tests with long post-exposure periods. Various studies have reported the toxicological effects of one or more compounds in organisms [37,54]. However, studying the synergism or antagonism that may occur with the presence of contaminants and environmental parameters (pH, dissolved oxygen, turbidity) in organisms is complex [55]. Prolonged exposure to these metals can cause cell death and alterations in DNA, lipids, proteins, enzymes, and homeostasis of calcium and sodium ions [56]. For example, 40 mg L−1 Fe3+ has been shown to cause 100% mortality in Dugesia japonica at 25 ◦C; additionally, the low temperature could slow down the effect of Fe3+ on planarian toxicity, and at a suitable temperature, the toxic effects of Fe3+ on planarian can be accelerated [57]. Heavy metals, such as, Zn, Cu, and Fe, are necessary for the proper functioning of various enzymes and proteins. However, when the same metals accumulate above the threshold, they become toxic. This induces the generation of reactive nitrogen and oxygen species (RNS; ROS), which results in the peroxidation of lipids in the plasma membrane [23,58]. Reports show heavy metal bioaccumulation in organisms through food chains [59,60]. It has been shown that the enzymatic activity of superoxide dismutase and catalase can play an important role on glutathione peroxidase in the antioxidant defense system of Dugesia japonica in response to exposure to copper [38]. Another study conducted with Girardia schubarti suggests that copper could modulate the genotoxic effects associated with the exposure of complex mixtures in the environment [39]. Furthermore, in our work we found concentrations of up to 0.88 mg L−1 of dissolved iron with the temperature in the Tocantins state fluctuating between 30 and 38 ◦C. In the field conditions, temperatures above 27 ◦C could cause mortality and slow movements in G. tigrina; consequently, the species releases mucus to change the surrounding pH of its external environment to maintain its physiological function [23]. High levels of dissolved aluminum (point 7), total chlorine (points 4 and 11), and zinc (point 5) were found in water samples of TAHR, which may be associated with the intensive and periodic use of fertilizers and agricultural correctives (in the case of aluminum), whereas it is known that freshwater planarians can present different responses to heavy metals. The high toxicity of aluminum, if compared to chromium and cadmium, causes uncoordinated writhing in exposed planarians, suggesting that neurotoxic effects were produced in intact and regenerating Dugesia estrusca [40]. Furthermore, chlorine plays a key role in disinfecting drinking water and wastewater; on the other hand, it represents a Water 2021, 13, 1077 9 of 13 risk to the freshwater ecosystem when used for a longer period [28]. These authors report the chronic effect of chlorine on Girardia tigrina with observed effect concentrations (LOEC) of 210 µg/L for feeding and pLMV, using the same methodology of our assays, as well as LOEC of 168 µg/L for head regeneration and 263 µg/L for reproduction (fertility and fertility). This is worrying from an environmental point of view, since at the sample of point 11 of TAHR, we found concentrations of total chlorine of 70 µg/L—the same order of magnitude as the LOEC values reported by Rodrigues Macêdo and co-authors [28]. On the other hand, zinc exposures have been reported to cause oxidative damage in aquatic organisms, for example, in the shrimp Atyaephyra desmarestii, while the feeding rate of amphipod Echinogammarus meridionalis was severely reduced with zinc exposures [60]. The authors report that a decrease in feeding rates reduces the total energy available, and the processes of metabolism and detoxification are also likely to be reduced. We did not measure oxygen levels during experimental feeding and locomotion tests, since the exposure occurred in 96 h in a shallow, flat vessel (Petri dish). In spite of this, the results of the analysis of the samples collected in the field revealed low concentrations of dissolved oxygen, mainly in the water samples of points 5 and 11. Although we cannot say that the effects on the feeding of planarians are related to low concentrations of oxygen, we speculate whether the effects observed in pLMV could be related, among other factors, to low oxygen concentrations in samples 5 and 11. It has been reported that low respiration rates can affect the physiological performance of freshwater invertebrates and have been associated with changes in behavior [37,61,62]. During moderate stress, maintenance costs increase to meet the additional energy demands for stress protection and damage repair, or metabolism and/or food assimilation is affected by the stressor. As a result, the aerobic range decreases [53,63]. Increases in temperature (as occur in TAHR-tropical climate) can lead to an increased metabolic rate and O2 consumption by aquatic organisms and the consequent production of reactive oxygen species (ROS) [64,65]. For example, studies in Girardia dorotocephala and Schmidtea mediterranea show that as the temperature increases, oxygen consumption will also increase [66]. Studies in G. tigrina show that it decreases pLMV when exposed to xenobiotics, for example, pLMV displayed a dose-dependent negative correlation with scopolamine con- centrations from 0.001 to 1.0 mM, and a further increase in scopolamine concentration to 2.25 mM did not further decrease pLMV [67]. In another study, galantamine showed high anticholinesterasic activity when compared to the other drugs, with a reduction in pLMV, presenting screw-like movement and hypokinesia, with a pLMV of 65 crossed lines during 5 min [68]. The pLMV seems to be a good indicator when exposed to xenobiotics, as shown by experiments carried out where, as the concentration increases, the locomotion speed of the planaria decreases [35–37,54]. This is also demonstrated in our study, where pLMV decreases in local (2–5, 7, 10–11) sites with the presence of xenobiotics. It should be considered that alterations in the behavior of the planarian can affect the food chain. The stability of a species has been shown to be highest when it is at the top of the food chain, and lowest when it is just below the top level, and it exhibits a switching pattern at intermediate levels [69]. Consequently, we could mention that the decrease in the feeding rate and the pLMV could be a consequence of the reallocation of energy to the stress response and the maintenance of homeostasis in planarian. The study of these biomarkers of behavior in the planarian suggests that the trophic chains in the freshwater ecosystems of the TAHR are being altered, since these organisms play a fundamental role in these ecosystems. Likewise, the results of this study alert us to the need to monitor the consequences of anthropic actions and agricultural pressure in the state of Tocantins—Brazil. At the same time, behavioral tests used with planarians seem to be fast screening tools that contribute to the biomonitoring of freshwater systems and further conservation measures to be taken in the Tocantins-Araguaia hydrographic system. In sum, the tributaries of the Tocantins-Araguaia hydrographic region, comprising the municipalities of Formoso do Araguaia, Lagoa da Confusão, Gurupi, and Porto Nacional, presented contamination by heavy metals and other pollutants, which caused deleterious Water 2021, 13, 1077 10 of 13 effects in behavioral responses of the freshwater planarian G. tigrina. Finally, this research provides an important approach to assess the ecological effects of contaminants in lotic ecosystems, using the behavior of planarians to assess water quality in tropical aquatic systems subjected to anthropic pressure. We aimed to use a behavioral tool that could predict deleterious effects of water samples from the environment even without knowing the physical or chemical properties of water. This would help to identify the impacted hotspots in a fast and cost-effective way. Obviously, further biomonitoring would be necessary on those hotspots for the identification of the environmental problems. Briefly, our goal was to use a behavioral biomarker to assess the sublethal effects of water contamination. The use of a behavioral test presents the advantage of being cumulative and integrative, i.e., it is caused by insufficient energy allocation for behavior due to its use for other processes altered by stress conditions, and that might be a chemical compound, an abiotic factor, or even the conjugation of several factors. 5. Conclusions The development of agriculture in the hydrographic Tocantins-Araguaia region con- tributes to the increased concentrations of metals, causing deleterious effects on benthic organisms, such as G. tigrina, that potentially affect various organizational levels of the trophic chain. The exposure in the laboratory of planarians to water of different sampling points in the hydrographic region Tocantins-Araguaia caused a reduction in the feeding rate and pLMV. The use of these cumulative and integrative behavioral biomarkers showed high sensitivity to contaminants and abiotic factors of water samples. These results emphasize the importance of evaluating biomarkers of environmental contamination, using the behavioral parameters of G. tigrina as fast screening tools in order to help the development and ecological relevance of biomonitoring programs in contaminated watersheds. Author Contributions: Conceptualization, R.A.S. and A.M.V.M.S.; methodology, A.M.C.L. and A.d.S.S.; software, A.M.C.L. and A.d.S.S.; validation, C.G., R.A.S. and A.M.V.M.S.; formal analysis, C.G.; investigation, A.M.C.L. and A.d.S.S.; resources, R.A.S. and A.M.V.M.S.; data curation, A.d.S.S.; writing—original draft preparation, A.M.C.L. and A.d.S.S.; writing—review and editing, all authors; visualization, C.G.; supervision, R.A.S. and A.M.V.M.S.; project administration, R.A.S.; funding acquisition, R.A.S. All authors have read and agreed to the published version of the manuscript. Funding: This work was supported by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior-CAPES, Brazil (Edital 71/2013–Programa Ciência Sem Fronteiras–Modalidade Pesquisador Visitante Especial-PVE–Projeto: A058_2013). Thanks are also due to FCT/MCTES for the financial sup- port to CESAM (UIDP/50017/2020 + UIDB/50017/2020), through national funds, and the co-funding by the FEDER, within the PT2020 Partnership Agreement and Compete 2020. Renato A. Sarmento received a scholarship from Conselho Nacional de Desenvolvimento Científico e Tecnológico-CNPq, Brazil (Produtividade em Pesquisa-Projeto: 306652/2018-8). Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: The data presented in this study is available in the current manuscript, raw data is available on request from the corresponding author. 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