UNIVERSIDADE ESTADUAL PAULISTA “JÚLIO DE MESQUITA FILHO” INSTITUTO DE BIOCIÊNCIAS – RIO CLARO unesp PROGRAMA DE PÓS-GRADUAÇÃO EM CIÊNCIAS BIOLÓGICAS (BIOLOGIA CELULAR, MOLECULAR E MICROBIOLOGIA) EXPRESSÃO GÊNICA DIFERENCIAL DOS TRANSCRIPTOMAS DE TÚBULOS DE MALPIGHI DE Melipona scutellaris EXPOSTOS AO TIAMETOXAM LUCAS MIOTELO Rio Claro – SP 2022 UNIVERSIDADE ESTADUAL PAULISTA “JÚLIO DE MESQUITA FILHO” INSTITUTO DE BIOCIÊNCIAS – RIO CLARO unesp PROGRAMA DE PÓS-GRADUAÇÃO EM CIÊNCIAS BIOLÓGICAS (BIOLOGIA CELULAR, MOLECULAR E MICROBIOLOGIA) EXPRESSÃO GÊNICA DIFERENCIAL DOS TRANSCRIPTOMAS DE TÚBULOS DE MALPIGHI DE Melipona scutellaris EXPOSTOS AO TIAMETOXAM LUCAS MIOTELO Dissertação apresentada ao Instituto de Biociências do Câmpus de Rio Claro, Universidade Estadual Paulista, como parte dos requisitos para obtenção do título de Mestre em Biologia Celular, Molecular e Microbiologia. Orientador: Prof. Dr. Osmar Malaspina Co-orientadora: Dra. Milene Ferro Rio Claro – SP 2022 M669e Miotelo, Lucas Expressão gênica diferencial dos transcriptomas de túbulos de Malpighi de Melipona scutellaris expostos ao tiametoxam / Lucas Miotelo. -- Rio Claro, 2022 82 p. : il., tabs., fotos Dissertação (mestrado) - Universidade Estadual Paulista (Unesp), Instituto de Biociências, Rio Claro Orientador: Osmar Malaspina Coorientadora: Milene Ferro 1. Abelha sem ferrão. 2. Destoxificação. 3. Neonicotinóides. 4. Montagem de novo. 5. Sequenciamento. I. Título. Sistema de geração automática de fichas catalográficas da Unesp. Biblioteca do Instituto de Biociências, Rio Claro. Dados fornecidos pelo autor(a). Essa ficha não pode ser modificada. Agradecimentos À FAPESP (Fundação de Amparo à pesquisa do Estado de São Paulo), pela bolsa de mestrado concedida (Processo: nº 2020/03527-3) e pelo apoio financeiro ao projeto de pesquisa (Processos: nº. 2017/21097-3), que possibilitou a realização desse estudo. Ao Centro de Estudos de Insetos Sociais (CEIS) e ao Departamento de Biologia Geral e Aplicada da UNESP (campus Rio Claro) pelo apoio técnico fornecido. Ao Prof. Dr. Osmar Malaspina, por ter me convidado a conhecer seu grupo de pesquisa (LECA) na primeira semana de graduação. Obrigado por ter alimentado minha curiosidade sobre o fantástico mundo das abelhas através dos livros que me emprestou, pelo incentivo e pelas oportunidades que tive ao longo de todos esses anos (e já são 9 anos!). À Dra. Milene Ferro, minha coorientadora, por me guiar durante o desenvolvimento do projeto. Sou muito grato pelos ensinamentos, pela paciência e dedicação diante das minhas infinitas perguntas e pedidos, não consigo imaginar esses dois últimos anos sem toda a ajuda e suporte que recebi. À Necis Miranda de Lima, sempre disposta a ajudar resolver os problemas burocráticos e por me mostrar que geralmente não são um bicho de sete cabeças. Aos membros do Laboratório de Ecotoxicologia e Conservação de Abelhas (LECA) que já partiram e aos que ainda continuam nessa jornada, obrigado pelos anos de trabalho e convivência. Em especial a Pâmela Decio por ouvir meus desabafos, por ter mantido e fortificado nossa amizade nos últimos anos. Sem você, sem nossas reclamações e cumplicidade, tenho certeza que o fardo desses anos teria sido mais pesado. As minhas alunas de iniciação científica que extrapolaram as fronteiras entre orientador e orientandas, contribuindo também com meu aprendizado pessoal. À Geovana Maloni por sempre estar comigo, nos melhores e piores momentos, e por basicamente compartilhar esse mestrado. Obrigado pelo apoio e paciência, e saiba que muitas vezes em meio ao desanimo a sua motivação e empolgação com a pesquisa me mantinham disposto a ir à luta mais uma vez. À Fernanda Souza por ter proporcionado reflexões e revoluções internas, por ter me feito enxergar o lado B entre as relações no ambiente de trabalho e também por me instigar a mudar alguns aspectos entre essas relações. À Júlia Italiani por me fazer desacelerar e dedicar meu tempo de forma mais leve. Não posso deixar de mencionar a Adna Dorigo, Tatiane Grella e a Annelise Rosa-Fontana pelas colaborações, risadas e ajudas ao longo desses anos. Aos membros do CEIS (Beto, Carol, Fram e a Amanda) que muitas vezes me socorreram na falta de um material e que caridosamente me compreendiam e ajudavam durante minhas peregrinações em busca de algo. À Amanda de Oliveira que além de amiga foi uma grande salvadora em diferentes momentos, sempre paciente e disposta a ajudar. Ainda precisamos de uma batata no Santa pra comemorar as vitórias dessa vida, reclamar e rir (claro, não poderíamos deixar esses aspectos de lado). Ao meu irmão Marcelo Miotelo e a minha mãe Rosa Miotelo pelo apoio em relação as minhas escolhas. Aos meus amigos Mari, Malu, Ana Luiza, Lara e Giovane pela compreensão nos meus momentos de ausência, pelo suporte emocional e motivação quase que diária. Ao Igor Otero, que dentre todos, é a única pessoa que realmente enxerga meus momentos de desespero, de fúria e teimosias (Em outras palavras, que eu me permito ser visto dessa forma). Obrigado por suportar comigo, por aliviar o estresse e se manter firme ao meu lado. Sei que nossas transições entre momentos difíceis e amenos nem sempre batem e que as vezes temos que dar suporte um ao outro mesmo quando não temos essa força toda, mas seguimos juntos, pacientes e tentando melhorar todos os dias. Por fim, agradeço a todos que contribuíram direta ou indiretamente para a realização deste trabalho e não foram mencionados, mas que se considerem no direito de estarem aqui. RESUMO No Brasil o consumo de inseticidas neonicotinóides, como o tiametoxam (TMX), é uma prática comum em culturas agrícolas. O uso indiscriminado de TMX afeta insetos não alvo, como as abelhas. Melipona scutellaris é uma espécie de abelha sem ferrão que foi inserida em uma lista do IBAMA, juntamente com o TMX, para que sejam realizados estudos toxicológicos. O presente estudo realizou uma análise de expressão gênica diferencial dos túbulos de Malpighi (Mt) de M. scutellaris expostas à CL50/100 do TMX por meio da análise transcriptômica. Além disso, foi avaliada a imunomarcação das proteínas de choque térmico (HSP) 70 e 90, juntamente com a busca por HSPs expressas no transcriptoma e a aplicação do método de TUNEL para detectar morte celular. Após a montagem de novo do transcriptoma, foram identificados 237 genes diferencialmente expressos (DEGs) e agrupados em nove clusters. Foram encontrados DEGs envolvidos em processos de destoxificação, excreção, regeneração tecidual, respiração celular, estresse oxidativo, apoptose, sinalização celular e sistema imune. A imunomarcação de HSP70 aumentou em um dia e diminuiu em oito dias de exposição ao TMX. Enquanto a HSP90 diminuiu em um dia e aumentou em oito. Já o método de TUNEL detectou fragmentação de DNA apenas em oito dias. Além disso, não existem DEGs relacionados a HSPs e por meio da análise de TPM (trascrits per milion) foi identificada que uma isoforma de HSP70 foi a proteína de choque térmico mais expressa. Considerando os resultados do transcriptoma, o metabolismo celular em Mt foi afetado principalmente após oito dias de exposição. Nove genes foram selecionados de diferentes clusters e validados por RT-qPCR. De acordo com nossos resultados, o TMX promove vários tipos de danos nas células dos Mt à nível molecular. Portanto, a interferência em diferentes processos celulares pode afetar diretamente a saúde de M. scutellaris, comprometendo funções essenciais dos Mt. Já os dados obtidos pela imunomarcação e análise do transcriptoma são conflitantes uma vez que não há nenhum DEG e a imunomarcação evidencia diferenças entre os grupos controle e exposto. Essas diferenças podem ser resultantes da alta sensibilidade desses imunomarcadores. O presente estudo foi o primeiro a avaliar os efeitos de um neonicotinóide na expressão gênica de uma abelha sem ferrão e evidencia a importância de análises moleculares para estudos ecotoxicológicos. Palavras-chave: Abelha sem ferrão, destoxificação, neonicotinóides, montagem de novo, sequenciamento, HSP70, HSP90, TUNEL. ABSTRACT In Brazil, using neonicotinoid insecticides, such as thiamethoxam (TMX), is common in crops. The indiscriminate use of TMX affects non-target insects such as bees. For example, Melipona scutellaris is a species of stingless bee that was included in an IBAMA list, along with TMX, for toxicological studies to be carried out. The present study analyzed differential gene expression of Malpighian tubules (Mt) of foragers bees of M. scutellaris exposed to LC50/100 of TMX through transcriptomic analysis. In addition, the immunostaining of heat shock proteins (HSP) 70 and 90 were evaluated, searching for HSPs expressed in the transcriptome and applying the TUNEL method to detect cell death. After de novo assembly, 237 differentially expressed genes (DEGs) were identified and grouped into nine clusters. DEGs involved in detoxification, excretion, tissue regeneration, cellular respiration, oxidative stress, apoptosis, cell signaling, and the immune system were found. HSP70 immunostaining increased within one day and decreased within eight days of exposure to TMX. At the same time, HSP90 decreased by one day and increased by eight. The TUNEL method detected DNA fragmentation only in eight days. In addition, there are no DEGs related to HSPs, and through the analysis of TPM (transcripts per million), it was identified that HSP70 was the most expressed heat shock protein. Regarding the transcriptome results, cell metabolism in Mt was mainly affected after eight days of exposure. Nine genes were selected from different clusters and validated by RT- qPCR. According to our results, TMX promotes several types of damage in Mt cells at the molecular level. Therefore, interference in different cellular processes directly affects the health of M. scutellaris, compromising essential functions of Mt. The data obtained for HSPs (immunostaining and transcriptome analysis) are conflicting since there are no DEGs on the transcriptome. However, the immunostaining showed differences between the control and exposed groups. These differences may result from the high sensitivity of this immunomarkers. The present study was the first to evaluate the effects of a neonicotinoid on the gene expression of stingless bees and highlighted the importance of molecular analyzes for ecotoxicological studies. Keywords: De novo assembly, neonicotinoid, stingless bee, detoxification, sequencing, HSP70, HSP90, TUNEL. Sumário INTRODUÇÃO GERAL ........................................................................................................... 6 OBJETIVOS ............................................................................................................................. 12 Objetivo geral ........................................................................................................................... 12 Objetivos específicos ................................................................................................................ 12 Capítulo 1 ................................................................................................................................. 13 Capítulo 2 ................................................................................................................................. 52 CONSIDERAÇÕES FINAIS ................................................................................................... 74 Referências ............................................................................................................................... 74 6 INTRODUÇÃO GERAL Estima-se que existam cerca de 20.000 espécies de abelhas descritas no mundo (MICHENER, 2007); essa diversidade contribui para a realização de serviços ecossistêmicos, como a polinização, em diferentes ambientes (POTTS et al., 2016). No Brasil são descritas 244 espécies de abelhas sem ferrão (PEDRO, 2014) e segundo Roubik (2006), formam um grupo 50 vezes mais diverso do que o grupo das abelhas melíferas (e.x.: Apis mellifera africanizada Linnaeus, 1758). Dentre as abelhas sem ferrão, algumas espécies vêm sendo visadas para a exploração de mel (ALVES, 2013) ou para a inserção de colônias em sistemas agrícolas e/ou naturais a fim de utilizá-las como agentes polinizadores (CHAM et al., 2018). Em plantações agrícolas de interesse econômico, as abelhas sem ferrão podem efetivamente polinizar as seguintes culturas: morango, citrus, abacate, pêssego, girassol, açaí, dentre outras (KLEIN et al., 2020). Especificamente em culturas de tomate, urucum, berinjela e pimentão é necessário que o agente polinizador seja capaz de realizar a polinização por vibração (DE LUCA; VALLEJO-MARÍN, 2013). Ao contrário de A. mellifera, incapaz de efetuar esse tipo de polinização (DE LUCA; VALLEJO-MARÍN, 2013), as abelhas sem ferrão, como Melipona scutellaris Latreille, 1811, podem polinizar com sucesso plantas com deiscência poricida por meio da vibração da musculatura do tórax (KLEIN et al., 2020). M. scutellaris, pertencente ao gênero Melipona, é uma abelha sem ferrão nativa da região nordeste do Brasil, no entanto, é bem adaptada as condições ecológicas e climáticas do estado de São Paulo (PEDRO; CAMARGO, 1999). Além disso, é uma espécie de fácil manejo na qual a produção e comércio de alguns produtos de alto valor econômico, como o mel, própolis e o pólen vem sendo cada vez mais explorados (COSTA et al., 2015). Os meliponíneos, tribo a qual a espécie M. scutellaris pertence, polinizam cerca de 66% das 1.500 espécies cultivadas em áreas agrícolas no mundo (KREMEN; WILLIAMS; THORP, 2002). Mesmo não sendo o alvo dos agrotóxicos, as abelhas são expostas a essas moléculas por meio de diferentes rotas, como: néctar, pólen, lama/solo, cera, água, superfícies de plantas, dentre outras (BOYLE et al., 2019). Neste contexto, é necessário refletir como as mudanças antropogênicas afetam a saúde, a abundância e a diversidade das abelhas (BIESMEIJER et al., 2006; GOULSON et al., 2015; IMPERATRIZ-FONSECA; SARAIVA; JONG, 2006). Devido a expansão agrícola e o uso indiscriminado de agrotóxicos, estudos que visam entender como é a ação de agrotóxicos na vida destes organismos vêm sendo realizados pelo nosso grupo de 7 pesquisa e por grupos associados (COSTA et al., 2015; DOMINGUES et al., 2020; MIOTELO et al., 2021, 2022). No entanto, para M. scutellaris estudos ecotoxicológicos ainda são escassos. Tiametoxam - TMX (C8H10ClN5O3S) é um inseticida neonicotinóide derivado da nicotina, classificado como N-nitroguanidina (BASS; FIELD, 2018; TOMIZAWA; CASIDA, 2005); que age no sistema nervoso central como agonista nos receptores nicotínicos de acetilcolina. Em condições normais, a acetilcolina é facilmente hidrolisada pela enzima acetilcolinesterase (BASS; FIELD, 2018; FAIRBROTHER et al., 2014), no entanto, os neonicotinóides não são imediatamente degradados, promovendo a transmissão de impulsos nervosos de forma contínua e descontrolada, o que causa hiperexcitação do sistema nervoso central dos insetos, podendo resultar na morte do indivíduo (BASS; FIELD, 2018; EL HASSANI et al., 2008). Além disso, o tiametoxam apresenta características sistêmicas, portanto, mesmo quando usado no tratamento de sementes é possível encontrar resíduos no néctar e no pólen das plantas (FORD; CASIDA, 2008; GOULSON, 2013; THOMPSON et al., 2018). Como consequência da exposição a concentrações subletais do TMX, importantes funções para a sobrevivência das abelhas podem ser comprometidas, como: alimentação, forrageamento, mobilidade, orientação e aprendizado (DECOURTYE et al., 2009; FISCHER et al., 2014; GILL; RAMOS-RODRIGUEZ; RAINE, 2012; HENRY et al., 2012; LAYCOCK et al., 2012). Uma vez que o TMX é um inseticida neurotóxico, os estudos toxicológicos tendem a focar o cérebro como órgão alvo para análises. No entanto, quando as abelhas são expostas por via oral, o alimento contaminado percorre a rota de metabolização e excreção do composto no organismo, podendo atingir órgãos não alvo como o intestino e os túbulos de Malpighi (CRUZ- LANDIM, 2009; MIOTELO et al., 2022). Em abelhas, os túbulos de Malpighi são estruturas finas e alongadas responsáveis pela excreção; constituídos por uma faixa de células epiteliais que estão sobre uma lâmina basal. Liberam as excretas na região pilórica do tubo digestório e organizam-se livremente na cavidade abdominal (CRUZ-LANDIM, 2009). Este órgão entra em contato com o inseticida, com metabólitos do inseticida e com moléculas não metabolizadas, durante a rota de metabolização do composto. Além disso, segundo Miotelo e colaboradores (2022), baixas concentrações de TMX apresentam efeitos citotóxicos significativos para os túbulos de Malpighi de M. scutellaris. Os autores reportaram que a exposição subletal do TMX em um e oito dias causam os seguintes danos celulares: aumento de esferocristais, perca de microvilosidades na porção apical das células, desorganização do labirinto basal, perda de 8 material citoplasmático, núcleos com formato irregular e cromatina condensada. Esses danos podem comprometer processos essenciais para a sobrevivência de M. scutellaris, como a excreção e destoxificação. A função primária do sistema excretor está relacionada com a regulação da homeostase, consistindo em manter o meio interno de um organismo nas melhores condições possíveis para que ocorra um bom funcionamento celular (CRUZ-LANDIM, 2009). Para garantir a homeostase da célula é preciso manter constante os níveis de sais, água, pH, pressão osmótica e eliminar produtos potencialmente tóxicos (CRUZ-LANDIM, 2009). Por se tratar de um órgão pequeno e delicado, geralmente são realizados estudos para compreender como a morfologia das células é afetada quando expostas a algum agrotóxico. Em alguns casos os pesquisadores optam por análises utilizando microscopia de luz (FERREIRA et al., 2013; GRELLA et al., 2019; ROSSI et al., 2013) e/ou microscopia eletrônica de transmissão (CATAE et al., 2014; FERREIRA et al., 2013; FRIOL et al., 2017; MIOTELO et al., 2022). Em contraste com os efeitos morfológicos e fisiológicos, incluindo características relevantes sobre a população, pouco se sabe sobre os efeitos moleculares dos neonicotinóides em abelhas (CHRISTEN et al., 2018). Estudos que aplicam abordagens moleculares usam, quase que exclusivamente, a espécie modelo A. mellifera pois foi a primeira espécie de abelha a ter o genoma sequenciado (GROZINGER; ZAYED, 2020). Apesar disso, considerando o território nacional, ainda são escassos estudos moleculares até mesmo para A. mellifera. Por outro lado, existem estudos na Europa que elucidam os efeitos de concentrações ambientalmente relevantes de neonicotinóides, demonstrando que esses induzem efeitos transcricionais significativos em vários genes-chave associados à neurotoxicidade, formação de memória, respostas ao estresse, metabolismo e expectativa de vida, bem como a regulação do sistema imunológico em exposições de laboratório e de campo (CHRISTEN et al., 2018; CHRISTEN; BACHOFER; FENT, 2017; FENT et al., 2020; SHI et al., 2017). Os avanços nas tecnologias e ferramentas de sequenciamento de nova geração (NGS) superaram diversas limitações. As abordagens ômicas, como genômica populacional, transcriptômica e metagenômica, podem fornecer a resolução e a eficiência necessárias para compreender melhor o declínio nas populações de abelhas (GROZINGER; ZAYED, 2020). Os avanços das técnicas moleculares permitem identificar genes centrais, vias metabólicas e comunidades microbianas associadas a abelhas sob condições de estresse (GROZINGER; ZAYED, 2020). Estudos que visam analisar o transcriptoma (conjunto de transcritos expressos numa determinada condição) de um determinado organismo passaram a ser impulsionados a 9 partir da introdução do NGS (METZKER, 2009). Essa técnica permite avaliar sequencias de RNA convertidas em cDNA em larga escala, além de analisar fragmentos maiores de RNA com alto nível de precisão e sensibilidade (MARTIN; WANG, 2011; OZSOLAK; MILOS, 2010). A transcriptômica pode facilitar a compreensão das respostas moleculares, fisiológicas e comportamentais de abelhas sob condições de estresse, permitindo o desenvolvimento de abordagens que podem aumentar a resistência e resiliência dessas abelhas (GROZINGER; ZAYED, 2020). Estudos transcriptômicos utilizando NGS têm sido fundamentais na caracterização dos mecanismos moleculares e fisiológicos pelos quais as abelhas respondem a diversos estressores, além de fornecerem possíveis ferramentas para um diagnóstico rápido da saúde das abelhas (GROZINGER; ZAYED, 2020). Recentemente, os estudos que utilizaram análises de sequenciamento de RNA para avaliar mudanças nos padrões de expressão gênica foram conduzidos em abelhas parasitadas (ZANNI et al., 2017), infectadas com vírus (BRUTSCHER; DAUGHENBAUGH; FLENNIKEN, 2017), expostas a agrotóxicos (CHRISTEN; BACHOFER; FENT, 2017; FENT; SCHMID; CHRISTEN, 2020; SHI et al., 2017), induzidas a estresse nutricional (CORBY-HARRIS et al., 2014), expostas a múltiplos estressores (AZZOUZ-OLDEN; HUNT; DEGRANDI-HOFFMAN, 2018) e/ou submetidas a diferentes temperaturas (AMSALEM et al., 2015; DURANT et al., 2016; TORSON et al., 2017). No entanto, todos esses estudos foram realizados com diferentes subespécies de A. mellifera. Quando se trata da análise de organismos não-modelo é comum utilizar uma abordagem de montagem de novo do transcriptoma, uma vez que não há um genoma de referência para realizar a montagem das bibliotecas de transcritos (CHRISTEN et al., 2018). Dessa forma o método de novo configura uma boa estratégia para estudos de expressão gênica com a espécie de abelha M. scutellaris, uma vez que apenas o genoma mitocondrial da espécie está disponível (SILVERIO et al., 2014). A expressão gênica de um organismo pode variar com as condições ambientais, estado de desenvolvimento e tecido de origem (RUDD, 2003) e a avaliação da abundância dos diferentes transcritos pode estimar a expressão gênica de determinada célula ou tecido (BOUCK; VISION, 2007), permitindo a identificação de genes relacionados aos processos de intoxicação por neonicotinóides ou ainda reconhecer os genes relacionados aos processos de destoxificação em abelhas. Além disso, acessar os níveis de expressão de HSP e morte celular por apoptose nos túbulos de Malpighi de abelhas contaminadas a agrotóxicos e abelhas não contaminadas pode representar uma abordagem promissora para detectar e diagnosticar rapidamente insetos 10 contaminados com TMX (MALASPINA; SILVA-ZACARIN, 2006a). Quando as células são expostas à ambientes quentes, acima de suas temperaturas normais de crescimento, são produzidas chaperonas moleculares denominadas proteínas de choque térmico (HSP) (ALBERTS et al., 2015; CANDIDO, 2001). Essas proteínas foram descobertas em Drosophila melanogaster, porém, atualmente a síntese dessas proteínas é descrita como um fenômeno universal, uma vez que, ocorre em todas as espécies de animais e plantas estudadas (CANDIDO, 2001; ELEKONICH, 2009; ZHAO et al., 2010). São caracterizadas e nomeadas de acordo com seu peso molecular (SCHLESINGER, 1990) e, em insetos, são descritas quatro principais famílias de HSPs, sendo elas: HSP90, HSP70, HSP60 e as sHSPs de baixo peso molecular (16 – 27 kDa) (COLLIER; BENESCH, 2020; DUBREZ et al., 2020; FEDER; HOFMANN, 1999; KING; MACRAE, 2015). Também podem ser chamadas de proteínas de estresse pois células expostas a produtos químicos prejudiciais ou eventos que proporcionem estresse celular tendem a diminuir a síntese da maioria das proteínas, no entanto, a presença das HSPs aumenta (CANDIDO, 2001; KING; MACRAE, 2015). Este aumento pode ocorrer em resposta à estressores ambientais, infecções, luz UV, agrotóxicos, frio, calor, hipóxia, fome, dentre outros (DUBREZ et al., 2020; ZHANG; OHASHI; RIKIHISA, 1998). As HSPs são chaperonas dependentes de ATP, com exceção das sHSPs que são independentes e representam a primeira linha de defesa celular, prevenindo a desnaturação irreversível de proteínas enquanto as células estão submetidas a condições de estresse (BASHA; O’NEILL; VIERLING, 2012; KING; MACRAE, 2015). Neste contexto, sua principal função é manter as proteínas em um estado de conformação funcional, além de auxiliar no dobramento de novas proteínas sintetizadas (DUBREZ et al., 2020; KING; MACRAE, 2015). Embora as chaperonas dependentes de ATP também sejam capazes de redobrar e desagregar proteínas desnaturadas, algumas HSPs atuam como potentes proteínas antiapoptóticas. Após se associar e bloquear as principais proteínas apoptóticas, as HSPs mantem as células vivas durante eventos de estresse junto com processos de desenvolvimento e diferenciação (DUBREZ et al., 2020). A interação de HSPs com outras proteínas também pode influenciar processos essenciais como: síntese de proteínas, sinalização celular, transcrição e metabolismo (KING; MACRAE, 2015; SOTTILE; NADIN, 2018). Em resumo, as funções mais importantes atribuídas às HSPs são: transporte de proteínas para compartimentos celulares; dobramento de proteínas no citosol, mitocôndrias e retículo endoplasmático; prevenção de agregações de proteínas; controle de proteínas regulatórias; 11 degradação de proteínas instáveis; redobramento de proteínas mal dobradas e dissolução de complexos de proteínas (BUKAU; HORWICH, 1998). Dentre as principais famílias de HSPs, considerando a regulação da apoptose, HSP27 e HSP70 são denominadas antiapoptóticas (GARRIDO et al., 2001). A família da HSP70 é considerada o grupo mais conservado dentre todas as HSPs (BEERE; GREEN, 2001) e atuam em vários pontos nas rotas de sinalização de apoptose, sugerindo que sua ação determinará o destino das células sob estresse (BEERE et al., 2000; KURASHOVA; MADAEVA; KOLESNIKOVA, 2020; MOSSER et al., 2000; RAVAGNAN et al., 2001). Além disso, corrigem mudanças conformacionais em proteínas e contribuem com respostas primárias ao estresse oxidativo, protegendo proteínas e enzimas dos efeitos de EROs (KURASHOVA; MADAEVA; KOLESNIKOVA, 2020). Já as HSP90, embora também sejam produzidas durante eventos de estresse, ainda não existe um consenso se atuam de forma anti ou pró apoptose uma vez que respondem de maneiras diferentes à estresse (KING; MACRAE, 2015). Uma das técnicas amplamente utilizadas para avaliar a morte celular é o método TUNEL (Terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling) (GAVRIELI; SHERMAN; BEN-SASSON, 1992). Quando as células estão em processo de morte as endonucleases clivam o DNA em muitos fragmentos, gerando várias extremidades livres de DNA (ALBERTS et al., 2015). Consequentemente, o método TUNEL é capaz de detectar o dano usando a capacidade da enzima desoxinucleotidil transferase terminal (TdT) que transfere cadeias de desoxinucleotídeo marcados (dUTP) para os terminais 3'-hidroxil (3'-OH) dos fragmentos (GAVRIELI; SHERMAN; BEN-SASSON, 1992). Assim, o método TUNEL aliado as HSPs podem ser utilizados para entender como as células estão enfrentando os danos moleculares causados por concentrações ambientalmente relevantes de agrotóxicos e avaliar seu nível de severidade para as abelhas, pois ambos representam uma ótima alternativa para diagnóstico biológico rápido (MALASPINA; SILVA-ZACARIN, 2006b). 12 OBJETIVOS Objetivo geral O presente estudo visou realizar a análise dos genes diferencialmente expressos nos túbulos de Malpighi da abelha sem ferrão M. scutellaris submetidos à CL50/100 do inseticida TMX em dois períodos de tempo (um e oito dias). Além de identificar as possíveis alterações morfofisiológicas causadas pelo TMX nos túbulos de Malpighi de M. scutellaris, por meio da imunomarcação de proteínas de estresse celular e morte celular por fragmentação do DNA e correlacionar com os dados dos transcriptomas. Objetivos específicos - Identificar os genes diferencialmente expressos entre os grupos controle e TMX em um e oito dias de exposição a uma concentração subletal. - Identificar as vias metabólicas putativamente afetadas pelo TMX, com especial atenção às funções primárias dos túbulos de Malpighi: destoxificação, excreção e osmorregulação. - Avaliar genes que possam estar associados a estresse oxidativo e morte celular. - Analisar as possíveis alterações morfofisiológicas causadas pelo TMX nos túbulos de Malpighi por meio das técnicas de imunomarcação de HSP70 e HSP90. - Selecionar, no transcriptoma, apenas genes associados com HSPs e por meio da análise de TPM verificar quais HSPs estão sendo mais expressas. - Detectar indícios de morte celular por meio da técnica de TUNEL. 13 Capítulo 1 O artigo referente a este capítulo foi submetido para publicação na revista Science of the Total Environment. Portanto, está editado conforme as normas da revista. Transcriptomic analysis of Malpighian tubules from the stingless bee Melipona scutellaris reveals thiamethoxam-induced damages Lucas Miotelo a, *, 1, Milene Ferro a, 1; Geovana Maloni a; Igor Vinicius Ramos Otero a; Roberta Cornélio Ferreira Nocelli b; Mauricio Bacci a; Osmar Malaspina a a Department of General and Applied Biology, Institute of Biosciences, São Paulo State University (UNESP), Rio Claro, SP, Brazil. bCenter of Agrarian Sciences, Federal University of São Carlos (UFSCar), Anhanguera Road Km 174, Araras, SP, Brazil 1 These authors share the first authorship. Graphical Abstract 14 Highlights Melipona scutellaris was exposed to a sublethal concentration of thiamethoxam. More the 200 genes were differentially expressed in the presence of TMX. Malpighian tubules were selected as non-target organs for transcriptome analyses. Oxidative stress, energy metabolism, and cell death are pathways triggered by TMX. Abstract The concern about pesticide exposure to neotropical bees has been increasing in the last few years, and knowledge gaps have been identified. Although stingless bees, (e.g.: Melipona scutellaris), are more diverse than honeybees and they stand out in the pollination of several valuable economical crops, toxicity assessments with stingless bees are still scarce. Nowadays new approaches in ecotoxicological studies, such as omic analysis, were pointed out as a strategy to reveal mechanisms of how bees deal with these stressors. To date, no molecular techniques have been applied for the evaluation of target and/or non-target organs in stingless bees, such as the Malpighian tubules (Mt). Therefore, in the present study, we evaluated the differentially expressed genes (DEGs) in the Mt of M. scutellaris after one and eight days of thiamethoxam (TMX) exposure. Through functional annotation analysis of four transcriptome libraries, the time course line approach revealed 237 DEGs (nine clusters) associated with carbon/energy metabolism and cellular processes (lysosomes, autophagy, and glycan degradation). The expression profiles of Mt were altered by TMX in processes, such as detoxification, excretion, tissue regeneration, oxidative stress, apoptosis, and DNA repair. Transcriptome analysis showed that cell metabolism in Mt was mainly affected after 8 days of exposure. Nine genes were selected from different clusters and validated by RT-qPCR. According to our findings, TMX promotes several types of damage in Mt cells at the molecular level. Therefore, interference of different cellular processes directly affects the health of M. scutellaris by compromising the function of Mt. Keywords: De novo assembly, differentially gene expressed, excretion organ, neonicotinoid, sublethal effects. 15 Introduction Pollination by insects is a valuable ecosystem service predominantly provided by bees (Potts et al., 2016). Among the 20,000 bee species reported (Michener, 2007), approximately 244 stingless bees species are found in Brazil (Pedro, 2014). Melipona scutellaris (Latreille, 1811), a stingless bee species from northeast Brazil, can perform buzz pollination (De Luca and Vallejo-Marín, 2013). Buzz pollination is characterized by vibration resulting from contractions of the bee’s body muscles, thereby, releasing pollen grains (De Luca and Vallejo-Marín, 2013). Although Apis mellifera (Linnaeus, 1758) cannot perform buzz pollination, many stingless bee species significantly contribute to flowers with poricidal anthers, such as tomato, annatto, eggplant, and sweet pepper (De Luca and Vallejo-Marín, 2013; Klein et al., 2020). In fact, this bee species is especially relevant for Neotropical regions owing to its great potential as a commercial pollinator; this is because it is easily managed (Cham et al., 2018), and the production and commercialization of propolis, honey, and pollen can be of high economic value (Costa et al., 2015). In the last few decades, there have been reports of significant decline in bees diversity (Potts et al., 2016; Zattara and Aizen, 2021). Consequently, plant species diversity may decline, compromising food security (Biesmeijer et al., 2006; Potts et al., 2016). One of the causes of this decrease in bee diversity is related to agricultural landscapes and practices (Kremen et al., 2002; Potts et al., 2010). In this scenario, bees are exposed to several agricultural pesticides (Boyle et al., 2019), such as those within the neonicotinoid class (Bass and Field, 2018). Thiamethoxam (TMX) is a highly active neurotoxin that acts as an agonist of nicotinic acetylcholine receptors (AChRs) (Bass and Field, 2018), and affects the nervous system, compromising orientation, learning, and memory (Decourtye et al., 2004; Roat et al., 2020). Owing to the systemic characteristics of TMX, even if used in seed treatment, residues can be found in the nectar and pollen of flowers (Ford and Casida, 2008; Thompson et al., 2018). Sublethal exposure of TMX has been reported to affect the brain (Christen et al., 2018; Miotelo et al., 2022, 2021; Roat et al., 2020) and non-target organs, such as the midgut and Malpighian tubules (Mt) (Miotelo et al., 2022). Bees can come into contact with insecticides through different routes, such as particles in the air, mud/soil, water, plant surfaces, propolis/resin, nectar, and pollen (Boyle et al., 2019). Upon oral exposure, TMX can affect organs that are not their target, such as the Mt. Accordingly, the organs related to the routes of absorption, metabolism of pesticide residues, and excretion must be evaluated (Miotelo et al., 2022). Mt is responsible for osmoregulation, 16 excretion, and detoxification (Nocelli et al., 2016). Few studies have evaluated the cytotoxic effects of pesticides on Mt using light microscopy (Ferreira et al., 2013; Rossi et al., 2013) or transmission electron microscopy (Catae et al., 2014; Ferreira et al., 2013; Friol et al., 2017; Miotelo et al., 2022). However, to date, there is no available information regarding the molecular effects of TMX on this organ. Studies that apply molecular approaches almost exclusively use the model species, Apis mellifera Linnaeus 1758 (Grozinger and Zayed, 2020). These studies revealed the effects of environmentally relevant concentrations of neonicotinoids and the significant transcriptional changes in several key genes associated with neurotoxicity, memory formation, stress responses, metabolism, and lifespan (Christen et al., 2018, 2017; Fent et al., 2020; Shi et al., 2017). Next-generation sequencing and de novo transcriptome assembly enable advances in knowledge of non-model organisms (Grozinger and Zayed, 2020). The transcriptome helps to understand how bees respond to environmental stressors, showing molecular, physiological, and behavioral responses (Christen et al., 2018; Grozinger and Zayed, 2020). Since 2017, the Brazilian Institute for the Environment and Renewable Natural Resources (IBAMA) has stimulated research on stingless bees and neonicotinoids (IBAMA, 2017). An omics approach can improve the comprehension of stressors that undermine bee health. Further, the transcriptome allows the evaluation of mechanisms and pathways by which bees deal with these stressors (Grozinger and Zayed, 2020). According to Miotelo et al. (2022), the Mt of M. scutellaris displays ultrastructural damage when exposed to an environmentally relevant concentration of TMX. Therefore, the present study aimed to analyze the differentially expressed genes (DEGs) in the Mt of the stingless bee, M. scutellaris. Further, by using RNA- sequencing (RNA-seq) and time course analysis, we evaluated how TMX influenced gene expression and molecular pathways at two different times of exposure while promoting several damages in Mt cells. To our knowledge, this is the first study to employ transcriptome analyses to investigate the molecular effects of pesticides on stingless bees and non-target organs. Material and methods 2.1 Oral exposure to TMX Forager bees of M. scutellaris were collected from three healthy colonies in the meliponary of São Paulo State University (UNESP), Institute of Biosciences, Rio Claro, SP, Brazil. Bees were collected in 250 mL plastic cages containing holes side-drilled for air exchange. The experimental group consisted of 220 bees divided into two groups: a control group (110 bees) and a TMX group (110 bees). Thiamethoxam PESTANAL® 17 (C8H10ClN5O3S), an analytical standard (purity ≥98.0%), was purchased from Sigma-Aldrich and solubilized in water. The sublethal concentration of TMX was based on the mean lethal concentration of M. scutellaris (LC50 = 0.0543 ng a.i./μL), as determined by Miotelo et al. (2021). A stock solution of 1000 ng of TMX was prepared (10 mg of TMX in 10 mL of deionized water) and subjected to serial dilution to achieve the desired concentration (LC50/100 = 0.000543 ng a.i./μL). A sugar solution (water and sugar: 50% w/v) was used to perform the serial dilutions. Of note, the control group only received a sugar solution without any contaminants. Microtubes (2 mL) containing side-drilled holes were provided as feeders, and syrup was provided ad libitum. After exposure to TMX, the experimental cages were kept in an incubator (chamber of biochemical oxygen demand, B.O.D) at 28 ± 2 ºC, relative humidity of 70 ± 05%, and constant darkness. The exposure assay was carried out according to the recommendations of the Organization for Economic Cooperation and Development (OECD) (1998), with adaptation to stingless bees. Based on the mean lethal time determined by Miotelo et al. (2022), the bees were exposed to TMX for eight days and the molecular influence of the insecticide was evaluated after one and eight days of exposure. 2.2 RNA extraction Mts were dissected after one and eight days of exposure to TMX. On each day of the dissection, 27 bees from each group were employed. The control and TMX groups had three microtubes containing a pool of nine bees each (three bees per colony). The organs were stored in RNAlater throughout the dissection process. Total RNA was extracted using the QIAGEN® RNeasy Mini Kit, according to the manufacturer’s instructions. RNA integrity was verified via agarose gel electrophoresis (1% w/v). Samples with total RNA were sent to Macrogen (South Korea) for purity and concentration quality control. Macrogen also constructed a cDNA library (TruSeq stranded mRNA library). Thereafter, sequencing was performed using Illumina NovaSeq6000, paired-end 2 × 100 bp, according to the manufacturer’s protocol (Macrogen, South Korea). 2.3 Preprocessing reads, de novo assembly, and functional annotation The FastQC tool provided by Babraham Bioinformatics was used for read control (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/). A common phenomenon, known as deviation in the GC content, was observed at the beginning of the reads; this was derived from sequencing on the Illumina platform (Conesa et al., 2016; Hansen et al., 2010). Briefly, cuts were made in the first 15 nucleotides of all reads; this removal was performed using the fastx_trimmer tool available in the FASTXToolkit http://www.bioinformatics.babraham.ac.uk/projects/fastqc/ 18 (http://hannonlab.cshl.edu/fastx_toolkit/index.html). Low-quality raw reads (Phred Q score <30) were trimmed using the SeqyClean software (https://github.com/ibest/seqyclean) (Zhbannikov et al., 2017). The normalization protocol incorporated in Trinity (version 2.2.0) (Grabherr et al., 2013) was applied to increase the efficiency of assembly reads (Brown et al., 2012). The libraries were de novo assembled using Trinity default parameters. At the end of de novo assembly, the completeness of the assembly was evaluated using BUSCO v.5 (Waterhouse et al., 2018) based on gene databases containing universal single-copy orthologs (OrthoDB) for the order, Hymenoptera_odb10. 2.4 Differential gene expression analysis Bowtie2 tool (Langmead and Salzberg, 2012) and RSEM (Li and Dewey, 2011) were used to map and quantify the reads of each library in the assembled reference transcriptome. This process was performed using the OmicsBox software (BioBam, Valencia, Spain) (Götz et al., 2008). Differential expression analysis was performed using the maSigPro tool in the OmicsBox software to verify related changes over the time of exposure to the insecticide and between the experimental groups using the time-course expression approach (Nueda et al., 2014; Pradhan et al., 2020). DEGs were grouped into nine clusters. Gene annotation was performed on OmicsBox using BlastX (Altschul et al., 1990) with an E-value of 1e-03 against the NCBI nonredundant (NR) database. Gene Ontology (GO) functional classifications into the three main categories were carried out: Biological Processes (BP), Molecular Function (MF), and Cell Component (CC). Domain proteins were found with InterProScan (Zdobnov and Apweiler, 2001), followed by the attribution of Enzyme Commission (EC) terms. Kyoto Encyclopedia of Genes and Genomes (KEGG) annotation was performed to obtain pathway annotations for the DEGs (Christen et al., 2018). 2.5 Gene validation by RT-qPCR The DEGs selected for validation by qRT-PCR were P450 9e2, SUN1, BAI1, BolA, D3PD, AQP, UDP, and ADAM-17 (Supplementary table 1). The previously extracted RNA (see the section on RNA extraction) was used for cDNA synthesis using the RevertAid H minus First-Strand cDNA Synthesis Kit (Thermo Scientific, USA). Samples containing 1646 ng of total RNA were used to validate the RNA sequencing data. Each selected gene was applied in quadruplicate (technical replicates), and no template control (NTC) was used. The reaction mixture (20 μL) was added to each well. This mixture contained 10 μL Power Track SYBR Green Master Mix (Applied Biosystems), 1 μL of each gene-specific primer (Forward and Reverse), 0.6 μL of cDNA, and 0.5 μL of 40x inert yellow dye (SYBR Kit). Gene-specific http://hannonlab.cshl.edu/fastx_toolkit/index.html https://github.com/ibest/seqyclean 19 primers were designed using the Gene Runner software (Version 6.5.52). The qRT-PCR cycling conditions were as follows: holding stage of 95 °C for 3 min, followed by 40 cycles of denaturation at 95 °C for 30 s, and annealing/extension at 60 °C for 30 s. Melt curve analysis of each primer was performed following PCR amplification to rule out the possibility of primer- dimers and non-specific product formation. Ribosomal protein s5 was used as the reference gene for data normalization. The comparative 2−ΔΔCt method (based on CT values) was used to determine the expression level of each gene. Differences between treatments were assessed using one-way ANOVA followed by Tukey’s test to compare treatment means with respective controls. Differences were considered statistically significant at p < 0.05. 2.6 Accession numbers The raw sequence data from the transcriptome of Mts of M. scutellaris are available in the Short Read Archive (SRA) GenBank database: BioProject (PRJNA836917), BioSample (SAMN28188996–SAMN28188998, SAMN28189016–SAMN28189021, SAMN28189023– SAMN28189025), and SRA (SRR19178717–SRR19178728). Results 3.1 Transcriptome assembly After cleaning raw reads, normalizing, and performing de novo assembly, 97,706 contigs and 58,208 genes with a GC content of 37.16 were identified. In addition, an N50 value of 3736 was obtained. BUSCO software revealed the completeness and integrity of the assembled transcriptome against the Hymenoptera ortholog bank, indicating that 84% of the genes were complete (single-copy and duplicated). 3.2 DEGs Using time course analysis, 237 DEGs with significant temporal expression changes and differences between treatments (control and TMX group) were identified and divided into nine clusters (Figure 1). Genes in clusters two, three, four, six, and nine were upregulated after one day of exposure to TMX, and those in clusters four, six, eight, and nine were upregulated after eight days. Although clusters five and seven were downregulated after one day of exposure to TMX, clusters one, two, three, and five were downregulated after eight days. There was no difference in the expression of the genes in clusters one and eight after one day of exposure, and cluster seven after eight days of exposure. To perform further analysis, all non-annotated (NA) genes were removed, and 74 DEGs were selected as genes of interest, as shown in Table 1. 20 Figure 1 - Time course analysis showing differentially expressed genes grouped in clusters. Each plot represents a cluster of genes according to their average expression profile. Dots show the average expression values for each sample (blue and red dots and lines represent the control and TMX groups, respectively). Lines connect the average value of the gene expression at each time point. A – cluster one, B – cluster two, C- cluster three, D – cluster four, E – cluster five, F – cluster six, G - cluster seven, H – cluster eight and I – cluster nine. 21 Cluster 1 Gene ID Description E-value 1 day 8 days Function Abbreviation TRINITY_DN9117_c0_g1_i1 DNA replication complex GINS protein SLD5 3,80E-155 * - Tissue regeneration GINs TRINITY_DN7900_c0_g3_i1 BolA-like protein 3 1,73E-61 * - Detoxification BolA TRINITY_DN4348_c0_g1_i1 Longitudinals lacking protein, isoforms N/O/W/X/Y 2,55E-55 * - Signaling Lola1 TRINITY_DN10521_c0_g1_i1 NADH dehydrogenase subunit 5 1,61E-102 * - Cellular Respiration/Oxidative stress NADH5 TRINITY_DN17751_c1_g1_i1 Brain-specific angiogenesis inhibitor 1 4,26E-118 * - Phagocytosis/Apoptosis BAI1 Cluster 2 TRINITY_DN6431_c0_g3_i1 THO complex subunit 3 0 + - Oxidative stress/Apoptosis THO TRINITY_DN12574_c1_g1_i1 NADH dehydrogenase subunit 4 7,40E-93 + - Cellular Respiration/Apoptosis NADH4 TRINITY_DN9947_c0_g2_i1 Homocysteine S-methyltransferase YbgG-like 0 + - Osmoregulation/Stress BHMT TRINITY_DN8571_c0_g1_i1 Vacuolar protein sorting-associated protein 37B 5,95E-56 + - Protein degradation Vps37 Cluster 3 TRINITY_DN17485_c0_g5_i8 mpv17-like protein isoform X1 7,04E-114 + - Oxidative stress Mpv17 TRINITY_DN13120_c0_g1_i1 TGF-beta-activated kinase 1 and MAP3K7-binding protein 1- like isoform X1 0 + - Tissue regeneration TGFbeta TRINITY_DN17065_c0_g1_i4 Mitochondrial glycine transporter isoform X1 1,57E-167 + - Oxidative stress MGT TRINITY_DN16063_c1_g1_i10 SUN domain-containing protein 1 0 + - Nuclear morphology SUN1 TRINITY_DN12548_c0_g1_i3 Equilibrative nucleoside transporter 3 0 + - Immune system ENT TRINITY_DN17904_c1_g1_i13 Tyrosine kinase receptor Cad96Ca 0 + - Tissue regeneration Cad96Ca TRINITY_DN17904_c1_g1_i4 Non-homologous end-joining factor 1 1,76E-85 + - DNA repair NHEJ TRINITY_DN14444_c0_g1_i1 Monocarboxylate transporter 2-like 0 + - Energy metabolism MCT2 TRINITY_DN16944_c0_g1_i3 Spermatogenesis-associated protein 20 isoform X1 0 + - Oxidative stress SPATA20 TRINITY_DN15630_c0_g1_i3 Spindle pole body component 110-like 0 + - Cell division SPB TRINITY_DN17366_c0_g1_i8 Dynein regulatory complex protein 1 isoform X2 0 + - Cell division CD TRINITY_DN14214_c0_g1_i1 Tektin-4 0 + - Cell division Tektin-4 TRINITY_DN16528_c0_g1_i4 Inositol polyphosphate 1-phosphatase 0 + - Signaling/Stress INPP 22 TRINITY_DN17537_c0_g1_i21 Gastric triacylglycerol lipase-like 0 + - Energy/Resistance GTL TRINITY_DN16112_c0_g1_i1 Tetratricopeptide repeat protein 7B 0 + - Nuclear morphology TTC TRINITY_DN15105_c0_g1_i2 Cyclin-dependent kinase 12-like 0 + - Tissue regeneration CDK Cluster 4 TRINITY_DN17433_c0_g1_i1 UDP-glucuronosyltransferase 2B17-like 2,76E-34 + + Detoxification UDP TRINITY_DN17472_c2_g1_i4 Flocculation protein FLO11-like isoform X2 0 + + Cell adhesion FLO TRINITY_DN17474_c1_g1_i1 Facilitated trehalose transporter Tret1-like 0 + + Energy metabolism/Sugar source Tret1 TRINITY_DN18028_c2_g1_i5 EGF domain-specific O-linked N-acetylglucosamine transferase isoform X1 0 + + Cell adhesion EOGT TRINITY_DN9586_c0_g1_i1 AF4/FMR2 family member 4 isoform X1 0 + + Gene transcription/Splicing AF4 TRINITY_DN17043_c1_g1_i5 Insulin-like growth factor-binding protein complex acid labile subunit 0 + + Energy metabolism IGFs TRINITY_DN17982_c0_g2_i5 Succinate dehydrogenase [ubiquinone] flavoprotein subunit, mitochondrial 0 + + Energy metabolism SDH TRINITY_DN16465_c0_g1_i4 Glucose dehydrogenase [FAD, quinone]-like 0 + + Energy metabolism GDH-FAD TRINITY_DN13313_c1_g1_i3 Interferon-related developmental regulator 1-like 0 + + DNA Regulation and repair IFRD1 TRINITY_DN16684_c0_g2_i1 Collagen alpha-1(IV) chain 0 + + Tissue regeneration Col4A1 TRINITY_DN11297_c0_g1_i1 Defensin-2 precursor 5,18E-58 + + Immune system Defensin TRINITY_DN18434_c1_g1_i2 Titin isoform X2 0 + + Hemolymph filtration Titin TRINITY_DN17683_c1_g1_i1 ATPase H (+)-transporting accessory protein 2 isoform X3 8,08E-76 + + DNA repair Atp6ap2 TRINITY_DN17303_c0_g1_i8 Hamartin isoform X1 0 + + Tissue regeneration TSC1 TRINITY_DN17375_c0_g1_i4 ATP-binding cassette sub-family G member 5 0 + + Excretion ABCG5 TRINITY_DN17375_c0_g1_i11 Succinyl-CoA:3-ketoacid coenzyme A transferase 1, mitochondrial 0 + + Energy metabolism SCOT TRINITY_DN15526_c0_g1_i2 Monocarboxylate transporter 9 0 + + Excretion MCT9 TRINITY_DN15526_c0_g1_i6 Carboxypeptidase M 0 + + Removal of dead cells CPM TRINITY_DN14329_c0_g1_i1 Carboxypeptidase B-like 0 + + Removal of dead cells CPB TRINITY_DN15039_c0_g1_i2 Sodium-coupled monocarboxylate transporter 1 0 + + Energy metabolism MCT1 TRINITY_DN16559_c0_g1_i1 Protein NDRG3 isoform X2 3,60E-12 + + Oxidative stress NDRG3 TRINITY_DN16560_c0_g1_i2 MAGUK p55 subfamily member 7 isoform X1 0 + + Cell junction MPP7 23 TRINITY_DN12422_c0_g2_i1 ATP-binding cassette sub-family G member 4 0 + + Apoptosis ABCG4 TRINITY_DN16739_c0_g1_i1 Peroxidasin-like isoform X1 0 + + Tissue regeneration PXDN TRINITY_DN5497_c0_g1_i1 Regucalcin-like 1,95E-30 + + Anti-apoptosis. Regucalcin TRINITY_DN15325_c0_g1_i3 Esterase FE4 isoform X1 0 + + Detoxification/Oxidative stress Esterase FE4 TRINITY_DN10411_c0_g1_i1 Excitatory amino acid transporter 1 0 + + Signaling/Cytotoxicity EAAT1 TRINITY_DN16383_c2_g4_i2 Cytochrome P450 9e2 1,40E-33 + + Resistance to insecticides P450 9e2 Cluster 5 TRINITY_DN14745_c3_g1_i1 Protein NDRG3 2,5073E-13 - - Oxidative stress NDRG3 TRINITY_DN16163_c0_g1_i1 D-3-phosphoglycerate dehydrogenase 0 - - Protein synthesis D3PD Cluster 6 TRINITY_DN8149_c0_g1_i1 Protein phosphatase 1B isoform X1 1,97E-102 + + Apoptosis PTP-1B TRINITY_DN16819_c0_g1_i1 Longitudinals lacking protein, isoforms A/B/D/L-like isoform X9 1,39E-59 + + Signaling Lola TRINITY_DN13740_c0_g1_i4 ADAM 17-like protease 0 + + Tissue regeneration ADAM-17 TRINITY_DN14442_c0_g1_i2 tRNA guanosine-2'-O-methyltransferase TRM13 4,82E-93 + + Transcription regulation TRM13 TRINITY_DN18179_c3_g2_i1 Protein flightless-1 isoform X1 0 + + Tissue regeneration Flii TRINITY_DN18179_c3_g2_i10 Mitochondrial import receptor subunit TOM22 homolog 2,44E-49 + + Apoptosis TOM22 TRINITY_DN13818_c0_g1_i6 Procollagen-lysine,2-oxoglutarate 5-dioxygenase isoform X2 0 + + Tissue regeneration PLOD2 Cluster 7 TRINITY_DN18305_c0_g1_i1 Origin recognition complex subunit 3 8,43E-26 - * Tissue regeneration ORC TRINITY_DN18305_c0_g1_i2 Signal-induced proliferation-associated 1-like protein 2 isoform X1 0 - * Signaling SIPA TRINITY_DN18339_c2_g1_i2 Protein TAR1 1,22E-80 - * Oxidative stress TAR1 TRINITY_DN17944_c1_g4_i2 Tumor protein p53-inducible nuclear protein 2 isoform X1 7,31E-45 - * Protein degradation TP53INP2 TRINITY_DN6865_c0_g1_i1 Aquaporin isoform X1 1,65E-29 - * Excretion AQP TRINITY_DN16716_c1_g3_i1 Omega-conotoxin-like protein 1 1,07603E-12 - * Immune system ICK Cluster 8 TRINITY_DN12014_c0_g1_i1 ATP-dependent RNA helicase DDX51 1,97E-23 * + DNA repair DDX51 TRINITY_DN38669_c0_g1_i1 Alcohol dehydrogenase 1,18E-142 * + Oxidative stress ADN TRINITY_DN33225_c0_g1_i1 Glyceraldehyde-3-phosphate dehydrogenase 0 * + Oxidative stress GAPDH 24 Cluster 9 TRINITY_DN16635_c0_g1_i7 G-protein coupled receptor 0 + + Immune system GPCRs TRINITY_DN17254_c0_g1_i1 Codanin-1 8,60238E-09 + + Cell division Cod1 TRINITY_DN17254_c0_g1_i2 Cathepsin L 5,53E-33 + + Apoptosis Cat1 Table 1: Expression profile and putative function of the 74 DEGs of interest. Consider the abbreviations listed in this table for the results and discussion section. +: upregulation. -: downregulation. *: no difference. 25 3.3 Functional analysis of DEGs (GO term attribution) The potential function relevance of the DEGs was evaluated through function annotation by GO term attribution. The GO terms were classified in three categories: biological processes (BP), molecular functions (MF) and cellular components (CC) (Figure 2). In the nine clusters, the GO terms attribution revealed genes annotated mainly to 17 BP terms, 10 CC terms, and 5 MF terms. Figure 2 - Functional enrichment analysis of all time-course DEGs of M. scutellaris for each cluster. The GO terms include biological process, cellular component, and molecular function. The group of enzymes most expressed through the DEGs was hydrolases, followed by transferases, oxidoreductases, translocases, ligases, isomerases, and lyases (Figure 3). 26 Figure 3 – Enzyme Commission number (EC number) attributed to DEGs, showing the chemical reactions that they catalyze in each cluster. 3.4 KEGG To address the potential pathways in which the DEGs were involved, annotation was performed in the KEGG database. A total of 142 pathways were assigned to 52 unigenes. Table 2 shows the pathways with the highest number of attributed unigenes. The KEGG pathways mainly belonged to carbon metabolism, energy, signaling, and cellular processes. Several unigenes were also assigned to the immune system, amino acid metabolism, xenobiotic degradation, nervous system disorders, genotoxicity, and/or mutagenesis pathways. Pathways Sequence Protein/Enzyme Signaling AGE-RAGE signaling pathway in diabetic complications TRINITY_DN1760 6_c0_g1_i1 Tyrosine-protein kinase hopscotch isoform X1 TRINITY_DN1668 4_c0_g2_i1 Collagen alpha-1(IV) chain Glucagon signaling pathway TRINITY_DN1747 2_c2_g1_i4 Flocculation protein FLO11-like isoform X2 TRINITY_DN7320 _c0_g1_i1 Pyruvate dehydrogenase E1 component subunit beta, mitochondrial-like 1 2 3 4 5 6 7 8 9 0 10 20 30 40 50 60 70 80 C lu s te r Translocases Ligases Isomerases Lyases Hydrolases Transferases Oxidoreductases Attributed E.C (%) 27 Insulin signaling pathway TRINITY_DN1747 2_c2_g1_i4 Flocculation protein FLO11-like isoform X2 TRINITY_DN1730 3_c0_g1_i8 Hamartin isoform X1 Inositol phosphate metabolism TRINITY_DN1652 8_c0_g1_i4 Inositol polyphosphate 1-phosphatase TRINITY_DN1515 7_c1_g1_i1 Type II inositol 1,4,5-trisphosphate 5-phosphatase Phosphatidylinositol signaling system TRINITY_DN1652 8_c0_g1_i4 Inositol polyphosphate 1-phosphatase TRINITY_DN1515 7_c1_g1_i1 Type II inositol 1,4,5-trisphosphate 5-phosphatase PI3K-Akt signaling pathway TRINITY_DN1730 3_c0_g1_i8 Hamartin isoform X1 TRINITY_DN1668 4_c0_g2_i1 Collagen alpha-1(IV) chain TRINITY_DN1760 6_c0_g1_i4 Tyrosine-protein kinase hopscotch isoform X1 Imune system Hepatitis B TRINITY_DN1312 0_c0_g1_i1 TGF-beta-activated kinase 1 and MAP3K7- binding protein 1-like isoform X1 TRINITY_DN1760 6_c0_g1_i1 Tyrosine-protein kinase hopscotch isoform X1 Herpes simplex virus 1 infection TRINITY_DN1312 0_c0_g1_i1 TGF-beta-activated kinase 1 and MAP3K7- binding protein 1-like isoform X1 TRINITY_DN1730 3_c0_g1_i8 Hamartin isoform X1 TRINITY_DN1760 6_c0_g1_i1 Tyrosine-protein kinase hopscotch isoform X1 Human papillomavirus infection TRINITY_DN1730 3_c0_g1_i8 Hamartin isoform X1 TRINITY_DN1668 4_c0_g2_i1 Collagen alpha-1(IV) chain Leishmaniasis TRINITY_DN1312 0_c0_g1_i1 TGF-beta-activated kinase 1 and MAP3K7- binding protein 1-like isoform X1 TRINITY_DN1760 6_c0_g1_i1 Tyrosine-protein kinase hopscotch isoform X1 Toxoplasmosis TRINITY_DN1312 0_c0_g1_i2 TGF-beta-activated kinase 1 and MAP3K7- binding protein 1-like isoform X1 TRINITY_DN1760 6_c0_g1_i1 Tyrosine-protein kinase hopscotch isoform X1 Xenobiotic degradation/detoxification Drug metabolism - cytochrome P450 TRINITY_DN1743 3_c0_g1_i1 UDP-glucuronosyltransferase 2B17-like TRINITY_DN3866 9_c0_g1_i1 Alcohol dehydrogenase Drug metabolism - other enzymes TRINITY_DN1532 5_c0_g1_i3 Esterase FE4 isoform X1 TRINITY_DN5497 _c0_g1_i1 Regucalcin-like TRINITY_DN1743 3_c0_g1_i1 UDP-glucuronosyltransferase 2B17-like Metabolism of xenobiotics by cytochrome P450 TRINITY_DN1743 3_c0_g1_i1 UDP-glucuronosyltransferase 2B17-like TRINITY_DN3866 9_c0_g1_i1 Alcohol dehydrogenase Genotoxicity/mutagenesis Pathways in cancer TRINITY_DN1668 4_c0_g2_i1 Collagen alpha-1(IV) chain 28 TRINITY_DN1760 6_c0_g1_i1 Tyrosine-protein kinase hopscotch isoform X1 Carbon and/or energy metabolism Citrate cycle (TCA cycle) TRINITY_DN1798 2_c0_g2_i5 Succinate dehydrogenase [ubiquinone] flavoprotein subunit, mitochondrial-like TRINITY_DN7320 _c0_g1_i1 Pyruvate dehydrogenase E1 component subunit beta, mitochondrial-like Glycerolipid metabolism TRINITY_DN1488 0_c0_g1_i1 Dynein intermediate chain 2, axonemal TRINITY_DN1652 5_c0_g2_i1 Alpha-amylase-related protein Glycolysis / Gluconeogenesis TRINITY_DN7320 _c0_g1_i1 Pyruvate dehydrogenase E1 component subunit beta, mitochondrial-like TRINITY_DN3322 5_c0_g1_i1 Glyceraldehyde-3-phosphate dehydrogenase TRINITY_DN1869 3_c0_g1_i1 Class II fructose-bisphosphate aldolase TRINITY_DN3866 9_c0_g1_i1 Alcohol dehydrogenase Methane metabolism TRINITY_DN1809 4_c0_g2_i1 Serine-pyruvate aminotransferase, mitochondrial TRINITY_DN1616 3_c0_g1_i1 D-3-phosphoglycerate dehydrogenase TRINITY_DN1869 3_c0_g1_i1 Class II fructose-bisphosphate aldolase Oxidative phosphorylation TRINITY_DN1257 4_c1_g1_i1 NADH dehydrogenase subunit 4 TRINITY_DN1798 2_c0_g2_i5 Succinate dehydrogenase [ubiquinone] flavoprotein subunit, mitochondrial-like TRINITY_DN4159 6_c0_g1_i1 NADH dehydrogenase subunit 3 TRINITY_DN1052 1_c0_g1_i1 NADH dehydrogenase subunit 5 Pentose phosphate pathway TRINITY_DN5497 _c0_g1_i1 Regucalcin-like TRINITY_DN1869 3_c0_g1_i1 Class II fructose-bisphosphate aldolase Protein digestion and absorption TRINITY_DN1668 4_c0_g2_i1 Collagen alpha-1(IV) chain TRINITY_DN1432 9_c0_g1_i1 Carboxypeptidase B-like Pyruvate metabolism TRINITY_DN7320 _c0_g1_i1 Pyruvate dehydrogenase E1 component subunit beta, mitochondrial-like TRINITY_DN3866 9_c0_g1_i1 Alcohol dehydrogenase Ubiquinone and other terpenoid- quinone biosynthesis TRINITY_DN1052 1_c0_g1_i1 NADH dehydrogenase subunit 5 TRINITY_DN1257 4_c1_g1_i1 NADH dehydrogenase subunit 4 TRINITY_DN4159 6_c0_g1_i1 NADH dehydrogenase subunit 3 Aminoacids metabolism Cysteine and methionine metabolism TRINITY_DN9947 _c0_g2_i1 Homocysteine S-methyltransferase YbgG-like TRINITY_DN1809 4_c0_g2_i1 Serine-pyruvate aminotransferase, mitochondrial TRINITY_DN1616 3_c0_g1_i1 D-3-phosphoglycerate dehydrogenase 29 Glycine, serine and threonine metabolism TRINITY_DN9947 _c0_g2_i1 Homocysteine S-methyltransferase YbgG-like TRINITY_DN1809 4_c0_g2_i1 Serine-pyruvate aminotransferase, mitochondrial TRINITY_DN1616 3_c0_g1_i1 D-3-phosphoglycerate dehydrogenase TRINITY_DN3866 9_c0_g1_i1 Alcohol dehydrogenase Valine, leucine and isoleucine degradation TRINITY_DN1654 5_c0_g1_i1 Methylglutaconyl-CoA hydratase, mitochondrial TRINITY_DN1737 5_c0_g1_i11 Succinyl-CoA:3-ketoacid coenzyme A transferase 1, mitochondrial Cellular process Autophagy - animal TRINITY_DN1730 3_c0_g1_i8 Hamartin isoform X1 TRINITY_DN1794 4_c1_g4_i2 Tumor protein p53-inducible nuclear protein 2 isoform X1 TRINITY_DN1725 4_c0_g1_i2 Cathepsin L Lysosome TRINITY_DN1753 7_c0_g1_i21 Gastric triacylglycerol lipase-like TRINITY_DN2644 1_c0_g1_i1 Lysosomal acid glucosylceramidase-like isoform X3 TRINITY_DN1784 4_c2_g1_i2 Beta-galactosidase-like TRINITY_DN1869 3_c0_g1_i1 Class II fructose-bisphosphate aldolase TRINITY_DN1725 4_c0_g1_i2 Cathepsin L Other glycan degradation TRINITY_DN2644 1_c0_g1_i1 Lysosomal acid glucosylceramidase-like isoform X3 TRINITY_DN1784 4_c2_g1_i2 Beta-galactosidase-like TRINITY_DN1869 3_c0_g1_i1 Class II fructose-bisphosphate aldolase Peroxisome TRINITY_DN1748 5_c0_g5_i8 mpv17-like protein isoform X1 TRINITY_DN1809 4_c0_g2_i1 Serine-pyruvate aminotransferase, mitochondrial Retinol metabolism TRINITY_DN1743 3_c0_g1_i1 UDP-glucuronosyltransferase 2B17-like TRINITY_DN3866 9_c0_g1_i1 Alcohol dehydrogenase Sphingolipid metabolism TRINITY_DN2644 1_c0_g1_i1 Lysosomal acid glucosylceramidase-like isoform X3 TRINITY_DN1784 4_c2_g1_i2 Beta-galactosidase-like Thermogenesis TRINITY_DN1730 3_c0_g1_i8 Hamartin isoform X1 TRINITY_DN1798 2_c0_g2_i5 Succinate dehydrogenase [ubiquinone] flavoprotein subunit, mitochondrial-like Nervous system disorders Alzheimer disease TRINITY_DN1798 2_c0_g2_i5 Succinate dehydrogenase [ubiquinone] flavoprotein subunit, mitochondrial-like TRINITY_DN1374 0_c0_g1_i4 ADAM 17-like protease Cholinergic synapse TRINITY_DN1532 5_c0_g1_i3 Esterase FE4 isoform X1 30 TRINITY_DN1760 6_c0_g1_i1 Tyrosine-protein kinase hopscotch isoform X1 Table 2: The main KEGG pathways assigned to the differentially expressed unigenes 3.5 qPCR RT-qPCR was used to validate nine randomly selected DEGs (Figure 4). The P450 9e2, BAI1, and BolA genes were validated by qRT-PCR, and the results were concordant with data from the time-course analyses. The D3PD and AQA genes were validated after one day of TMX exposure, but did not show significant alterations after eight days of exposure based on qPCR. The UDP, ADAM-17, and Flii genes showed the same tendency of transcriptional changes between the transcriptome and RT-qPCR, although the alterations were not significant based on qPCR. The results for SUN1 (one day) and UDP and Flii (eight days) were not consistent with those of RNA-Seq analysis. The expression of the housekeeping gene (ribosomal protein s5) was unaltered after one and eight days of TMX exposure. Figure 4: Validation of the selected differentially expressed genes in the Malpighian tubules of the stingless bee, M. scutellaris, using qPCR. Gene expression levels were normalized to 31 those of ribosomal protein s5 and are presented as relative fold change compared with the respective levels in the control group after 1 and 8 days of exposure to TMX. The asterisk indicates a statistically significant difference (p < 0.05) between the control (blue) and TMX (red) groups. Discussion In 2012, the use of TMX was restricted by the European Union to crops that were attractive to bees, but was completely banned from all crops in 2018 (Bass and Field, 2018). Nonetheless, TMX is commercialized in North America and Latin America. In Brazil, this pesticide has been under environmental risk reassessment since 2017 by the Brazilian Institute for the Environment and Renewable Natural Resources (IBAMA) (IBAMA, 2017). Since then, researchers have been encouraged to investigate the effects of this molecule on stingless bees, a native South American bee group. Studies carried out with the model species, A. mellifera, revealed different effects induced by TMX using the following approaches: cytotoxic studies (Catae et al., 2014; Friol et al., 2017; Miotelo et al., 2021; Oliveira et al., 2013; Tavares et al., 2015), proteomic expression profile (Roat et al., 2020), alternative splicing (Decio et al., 2019, 2021b), enzymatic activity (Decio et al., 2021a; Tavares et al., 2017), immunohistochemistry (Tavares et al., 2019), and other approaches. However, studies on M. scutellaris are scarce (Miotelo et al., 2022, 2021). Further, no studies employed molecular techniques. In the present study, more than 200 genes were differentially expressed in M. scutellaris when the stingless bee was exposed to TMX. These DEGs were found to be involved in detoxification, excretion, tissue regeneration, cellular respiration, energy metabolism, oxidative stress, apoptosis, cell signaling, cell division, DNA repair, immune system, cell-cell adhesion, and nuclear morphology. To date, no study has investigated the molecular influence of TMX on non-target organs; however, Christen et al. (2018) evaluated the molecular effects of different neonicotinoids (including TMX) in the brain. Among the pesticides tested by these researchers, TMX was found to have the least effect on the gene expression profile. By considering the highest concentration tested, only 25 genes were found to have altered expression profiles owing to the influence of TMX, and these genes were mainly related to glucose metabolism. Excretion and detoxification are among the main functions of the Mt (Cruz-Landim, 1998). The transcriptome of M. scutellaris revealed three DEGs associated with detoxification (BolA, UDP, and esterase FE4). UDP belongs to an enzymatic family responsible for the 32 detoxification of xenobiotic compounds, making them more water-soluble (King et al., 2000; Tephly and Burchell, 1990). According to Pan et al. (2018), the upregulation of different members of this family may contribute to the detoxification of TMX in the cotton aphid, A. gossypii. The esterase FE4 has antioxidant properties in the presence of hydrogen peroxide or imidacloprid exposure (neonicotinoid insecticide). They also prevent damage caused by reactive oxygen species (ROS) (Ma et al., 2018). Thus, the upregulation of UDP and esterase FE4 after one and eight days of TMX exposure may represent a response of the Mt to detoxify the insecticide and protect cells from oxidative stress. However, BolA expression was downregulated after eight days. As BolA acts on responses to stressors (Cameron et al., 2011; Mil-homens et al., 2018), TMX could negatively interfere with other detoxification pathways. Regarding excretion, transcriptome analysis revealed three DEGs (ABCG5, MCT9, and AQP). ABCG5 aids in sterol excretion and is located in the apical area of cells, which is lined with the brush border (Cserepes et al., 2004; Klett et al., 2004; Nomura et al., 2021). ABCG5 promotes the excretion of xenobiotic compounds from cells into the lumen (Williams et al., 2021). MCT9 acts on the excretion of uric acid in healthy epithelial cells of the intestine and kidneys (Nakayama et al., 2013). As Mt produce a filtrate from the hemolymph called primary urine (Cruz-Landim, 1998), the upregulation of MCT9 and ABCG5 in one and eight days of TMX exposure can indicate a higher excretion level by the Mt. Although the Mt can recover from injury (Singh et al., 2007), the present study found 11 DEGs associated with tissue regeneration, including: GINs, TGFbeta, Cad96Ca, CDK, Col4A1, PXDN, TSC1, ADAM-17, Flii, PLOD2, and ORC. Tissue regeneration is also characterized by the formation and modulation of the basal membrane (Kovács et al., 2021). In Drosophila, Col4a1 is associated with the basal membrane of the Mt and acts on the maintenance of epithelial integrity (Kiss et al., 2016). PDXN participates in the synthesis of extracellular matrix and basal membranes (Kovács et al., 2021; Péterfi and Geiszt, 2014). ADAM-17 is the first defense against injury, and acts on the repair and regulation of tissue regeneration (Matthews et al., 2017; Scheller et al., 2011). PLOD2 is involved in post- transcriptional collagen modifications, is indispensable for the stability of the extracellular matrix, and can alter the arrangement of extracellular matrix fibers, and a consequently, affect cell morphology, adhesion, migration, and proliferation capacity (Cao et al., 2021; Du et al., 2017; Neyazi et al., 2017). These genes were upregulated at one and eight days of TMX exposure, possibly acting to regenerate on the Mts to recover from damage caused by the insecticide. TGB-beta and Cad96Ca exhibited the same pattern on day one and were 33 downregulated after eight days. In the kidneys, TGF-beta induces the production of collagen and fibronectin (Ma et al., 2022). Activation of Cad96Ca is essential to the stimulation of epithelial regeneration responses, as it promotes the assembly of actin filaments during tissue regeneration (Tsarouhas et al., 2014). This downregulation may represent failures in some regeneration pathways of the Mt. This event on day eight aligns with the results reported by Miotelo et al. (2022), as TMX is more harmful to the Mt cells after eight days of exposure. The transcriptome revealed two DEGs related to cellular respiration, NADH dehydrogenase subunits 5 and 4. Mitochondria generate energy for cells through the oxidative phosphorylation system. Complex I (NADH-dehydrogenase) belongs to this system and is the entry point for electrons in the respiratory chain (Grba and Hirst, 2020; Xue et al., 2019). Damage to complex I can compromise the ability of the respiratory chain to oxidize NADH to NAD (Seo et al., 2006). According to Xue et al. (2019), blocking cellular respiration causes an increase in the NADH/NAD+ ratio, which consequently increases the rates of O2 and other free radicals. Once complex I activity is disrupted, intracellular ROS levels increase (Murphy, 2009; Xue et al., 2019). The downregulation of NADH dehydrogenase subunits 4 and 5 after eight days of exposure to TMX can decrease cellular respiration, thereby increasing ROS levels in Mt cells, which corroborates the upregulation of UDP and esterase FE4 discussed previously. However, the overexpression of subunit 4 of NADH dehydrogenase is associated with its anti- apoptotic function (Ghosh and Girigoswami, 2008). Thus, the upregulation of subunit 4 after one day of exposure may represent a response of the organ to combat cell death. According to the literature, the Mt cells of M. scutellaris increase the number of mitochondria in the apical portion when exposed to TMX (Miotelo et al., 2022). Based on the results related to cellular respiration genes, the increase in mitochondria observed by Miotelo et al. (2022) may be a compensatory strategy of the cell induced by the energy deficit. Other genes also showed that the Mt cells were experiencing an energy deficit due to the upregulation of genes, such as MCT1 and MCT2, at one and eight days of TMX exposure. MCTs are membrane proteins that transport lactate, pyruvate, and ketone bodies (Pierre and Pellerin, 2009; Visser et al., 2007). A high concentration of lactate stimulates the upregulation of MCT2, which provides lactate to organs that require a greater energy demand (Medin et al., 2019). MCT1 overexpression is associated with glycolysis in cells with high energy demand (Kobayashi et al., 2021). Tret1, IGFs, SDH, GDH-FAD, and SCOT were found to be correlated with energy metabolism. Trehalose is the main sugar present in insect hemolymph and is a source of energy and carbon (Kikuta et al., 2012). In insects, the Mt have high concentrations 34 of soluble trehalose, which facilitates their conversion (regulated by Tret1) into glucose and its incorporation into cells, which requires energy (Kanamori et al., 2010; Kikuta et al., 2012). IGFs regulate circulating levels of trehalose and glucose by transferring these sugars from the hemolymph to the muscle or organ (Chowański et al., 2021). SDH and GDH-FAD are involved in oxidative phosphorylation, glycolysis, and carbohydrate homeostasis processes that generate energy (Moosavi et al., 2019; Okuda-Shimazaki et al., 2020). According to Acevedo et al. (2013), SDH is upregulated in organisms exposed to environmental stressors. SCOT catalyzes the conversion of acetoacetate to acetoacetyl-CoA, which is further metabolized via the citric acid cycle for energy production (Grünert et al., 2021). The upregulation of these genes at one and eight days could represent a response of the organ to increase energy production to compensate for the deficit caused by TMX cytotoxicity. The following nine DEGs were associated with oxidative stress: THO, Mpv17, MGT, SPATA20, NDRG3, TAR1, AND, and GAPDH. In insects, the THO complex responds to environmental stressors (Kim et al., 2011), specifically cellular stress (Moon and Chung, 2013). Mpv17 participates in the cellular antioxidant defense system (Iida et al., 2010; Krick et al., 2008). The overexpression of Mpv17 is related to cellular ROS levels (Iida et al., 2010). MGT facilitates the import of glycine into cells (Howard et al., 2010). Glycine has antioxidant properties and acts against ROS by increasing antioxidant enzymes, such as glutathione, catalase, and superoxide dismutase (Chen et al., 2018). SPATA20 is involved in compensatory oxidative stress responses and is upregulated under these conditions (Jarvis et al., 2020). The above genes were upregulated after one day and downregulated after eight days of TMX exposure. Thus, the Mts could increase the responses to oxidative stress in one day, and after continuous exposure for eight days, this organ may decrease these responses. Tar1 is downregulated when cellular respiration is defective, thereby avoiding severe consequences related to the presence of ROS (Bonawitz and Shadel, 2009). Therefore, considering the upregulation of Mpv17, MGT, and SPATA20 after one day, and the upregulation of UDP and esterase FE4 genes after one and eight days of exposure, TMX and/or its metabolites promote oxidative stress in the Mt cells. The following six DEGs were related to apoptosis: BAI1, ABCG4, TOM22, regucalcin, PTP-1B, and Cat1. The upregulation of PTP-1B induces cell death by apoptosis through the activity of cellular caspases (Takada et al., 2002) while the upregulation of ABCG4 is associated with apoptosis (Hegyi and Homolya, 2016). The upregulation of these genes on days one and eight may indicate that TMX promoted cell death. These results corroborate those of our 35 previous studies in which the morphological changes in the Mts caused by the same concentration of TMX were evaluated, which culminated in cell death (Miotelo et al., 2022). In contrast, regucalcin (upregulated on day one and eight) presents antiapoptotic effects by suppressing the signaling pathways that regulate apoptosis (Yamaguchi, 2013). Therefore, the regulation of apoptosis in the Mts is very complex, and different pathways may be involved. The transcriptome revealed five DEGs related to the signaling process: Lola1, INPP, EAAT1, Lola, and SIPA. Lola is a transcription factor involved in various axonal guidance decisions in the Drosophila nervous system. According to Goeke (Goeke et al., 2003), when the Lola isoform is compromised, damage occurs at a specific point on the axon. SIPA regulates synaptic signaling (Dolnik et al., 2016) and is essential for synaptic vesicle trafficking (Andres- Alonso et al., 2019). The downregulation of these genes at one and eight days can compromise cell signaling by preventing the reception of stimuli through neurotransmitters and result in the loss of communication between the Mts and neurons. In contrast, EAATs capture glutamate to aid in cell signaling processes and prevent cytotoxicity. The upregulation of EAATs on days one and eight may represent an increase in cell signaling to assist in events that may be cytotoxic to Mt cells. Among the few studies that assessed the possible molecular changes caused by TMX in A. mellifera, Roat et al. (2020) reported that sublethal exposure could affect cell signaling. Four DEGs, namely SPB, CD, Tektin-4, and Cod1, were associated with the cell division process. SPBs are important microtubule-organizing centers that are crucial for mitotic spindle assembly (Rüthnick and Schiebel, 2018). CD also acts on mitotic spindle assembly (Htet et al., 2020), and Tektin-4 is involved in the stability and structural complexity of microtubules in axonemes (Amos, 2008). The upregulation of these genes on day one could be an indication of the active process of cell division. However, as other genes indicate cell death and a decrease in tissue regeneration on day eight, the downregulation of SPB, CD, and Tektin-4 on day eight emphasizes the hypothesis that TMX compromises this process. Analysis of DEGs and KEGG pathways demonstrated that TMX and its derivative metabolites can affect DNA metabolism. Regarding DNA repair, the following DEGs were identified: Atp6ap2, DDX, and NHEJ. The overexpression of Atp6ap2 can compromise replication and DNA repair (Shibayama, 2020). DDX contributes to DNA repair by recruiting p53 (Nicol et al., 2013). During DNA damage, p53 triggers events, such as cell cycle arrest, DNA repair, or apoptosis (Zebian et al., 2022). The upregulation of Atp6ap2 on day one and eight can negatively affect DNA repair, and DDX can be an indication that TMX causes DNA 36 damage (genotoxicity). NHEJ is the main pathway for DNA damage repair and is triggered upon exposure to agents that culminate in DNA damage (Hefferin and Tomkinson, 2005). In the present study, this gene was upregulated after one day and could represent a response of the Mts to repair DNA damage caused by TMX. However, decreased NHEJ expression impairs DNA repair (Li et al., 2021). Thus, NHEJ downregulation on day eight is insufficient to correct the damage, which can also lead to cell death. Miotelo et al. (2022) reported that Mts changed the morphology of cells and nuclei after TMX exposure. In the present study, transcriptome analysis revealed two DEGs related to nuclear morphology (TCC and SUN1). TCC is an important factor in chromatin compaction and nuclear organization (El-Daher et al., 2018). The downregulation of TCC impacts nuclear morphology and destabilizes collagen adhesion (Jardine et al., 2019). SUN1 is localized in the inner nuclear membrane and is responsible for establishing physical connections between the nuclear envelope and cytoskeleton (Haque et al., 2006). These DEGs were upregulated on day one, indicating responses of Malpighian cells to maintain a stable nuclear morphology. However, after eight days, these DEGs were downregulated, possibly showing one of the origins that could destabilize the nuclear shape. Furthermore, changes in nuclear morphology can alter chromatin arrangement and trigger cell death, as reported by Miotelo et al. (2022). Different infection pathways were triggered in the presence of TMX according to KEGG analysis. Four DEGs, namely Defensin-2, ENT3, ICK, and GPCRs, were related to the immune system. Defensin-2 is responsible for individual immunity in bees (Ilyasov et al., 2012). Stress factors activate defense response pathways that induce defensin gene expression (Contreras et al., 2020). ENT3 assists in the development and proliferation of immune system cells (Wei et al., 2018). GPCRs recognize extracellular stimuli and act on responses related to infections or engulfing cells in apoptosis/necrosis. The upregulation of these genes on days one and eight indicated that M. scutellaris activated immune system responses against xenobiotic stressors. As the mean lethal time (LT50) of the LC50/100 (0.000543 ng a.i./μL syrup) is seven days for M. scutellaris, which indicates a 50% chance of bees dying in seven days, TMX is more harmful after eight days of exposure [19]. Our results show that oxidative stress was high on day one and continued to stress the cells after eight days. In addition, cell death triggered by PTP-1B and ABCG4 is associated with continuous exposure to TMX. Therefore, our results demonstrate that the highest cytotoxicity was achieved after eight days of continuous exposure to TMX. 37 Conclusion TMX affects the gene expression profiles in the Mts of M. scutellaris exposed to an environmentally relevant sublethal concentration of TMX. Among the 237 DEGs, TMX affected important pathways and promoted oxidative stress, cell damage and death, genotoxicity, and recovery impairment. Different cellular processes can be related to TMX exposure, such as detoxification, excretion, tissue regeneration, cellular respiration, energy metabolism, oxidative stress, apoptosis, cell signaling, cell division, DNA repair, immune system, and nuclear morphology. The eighth day of exposure resulted in changes in the gene expression profile, which is critical for the organ. Interference in these processes compromises the functioning of the Mts and can directly interfere with organ function, thereby directly affecting the health of the organism. Acknowledgments The authors would like to thank the São Paulo Research Foundation (FAPESP) for supporting this study with the grant (OM) 2017/21097-3 and the scholarships 2020/03527-3 (LM) and 2021/01359-9 (GM). We also would like to thank the Brazilian Federal Agency for Support and Evaluation of Graduate Education (CAPES), in the scope of the Program CAPES-PrInt, process number 88887.572722/2020-00, International Cooperation Project number 88887.310764/2018-00 (MF). Thanks to the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for the grant nº 400540/2018-5 (OM) and for the PhD scholarship nº 170714/2017-9 (IO). We also would like to thank Amanda de Oliveira for her guidance in the early stages of project development. Authorship contributions Lucas Miotelo: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Data Curation, Writing - Original Draft, and Visualization. Milene Ferro: Conceptualization, Methodology, Formal analysis, Investigation, Data Curation, Data Curation, Writing - Original Draft, and Visualization. Geovana Maloni: Validation, Investigation, and Writing - Review & Editing. Igor V. R. 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