Uma batalha antiga: os cientistas descobrem o que torna a malária um inimigo tão astuto
Plasmodium falciparum, o parasita que causa a forma mais letal de malária em humanos, é um mestre da evasão e se esquivou de todas as tentativas de uma vacina eficaz e durável. Agora, usando um método sofisticado que caracteriza como os anticorpos...
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)
Visão geral do PhIP-seq e pipeline de análise. A biblioteca de fagos falciparome exibe o proteoma de Plasmodium falciparum em peptídeos de 62 aa com tamanho de etapa de 25 aa no fago T7 e também inclui sequências variantes de muitos antígenos, incluindo os principais antígenos de superfície variantes (VSA). O PhIP-seq foi realizado com incubação da biblioteca Falciparome com plasma humano, seguido de IP dos anticorpos na amostra e enriquecimento do fago de ligação ao anticorpo. Duas rodadas de enriquecimento foram realizadas e os fagos enriquecidos foram sequenciados para obter a identidade dos peptídeos codificados. Um pipeline de filtragem foi então usado para identificar peptídeos sororreativos específicos para a coorte de malária. Crédito: eLife (2023). DOI: 10.7554/eLife.81401
Plasmodium falciparum, o parasita que causa a forma mais letal de malária em humanos, é um mestre da evasão e se esquivou de todas as tentativas de uma vacina eficaz e durável. Agora, usando um método sofisticado que caracteriza como os anticorpos respondem a todas as cerca de 5.400 proteínas do parasita, pesquisadores do Chan Zuckerberg Biohub–San Francisco (CZ Biohub SF) e da UC San Francisco (UCSF) criaram o primeiro mapa de alta resolução do resposta imune humana ao P. falciparum, oferecendo informações sobre o que torna esse parasita um patógeno tão persistente.
Em um estudo publicado na eLife em 10 de março, os pesquisadores empregaram um método sofisticado para quebrar as proteínas que compõem o P. falciparum em pedaços reconhecidos pelo nosso sistema imunológico e, em seguida, os expuseram ao sangue de 198 adultos e crianças de Uganda. Os resultados mostraram que os anticorpos se ligam a muitas regiões do P. falciparum que não geram uma resposta de anticorpos de longa duração, uma aparente "tática de desvio" que força o sistema imunológico a gerar respostas de vida mais curta.
"A malária é um profissional quando se trata de evasão imune", disse o presidente da CZ Biohub SF, Joe DeRisi, co-autor sênior do estudo. “Mas, em vez de usar furtividade, nossas novas descobertas sugerem que o parasita da malária está basicamente lançando um show de fogos de artifício que distrai o sistema imunológico, mantendo-o perseguindo alvos que, em última análise, não são úteis para desenvolver proteção a longo prazo”.
Um inimigo sofisticado
Quanto ao motivo pelo qual uma vacina durável contra a malária tem sido tão difícil de encontrar, os especialistas apontam para a complexidade do ciclo de vida do parasita. O P. falciparum muda profundamente à medida que se move pelo corpo humano , primeiro deslizando pela corrente sanguínea como um verme unicelular e depois se multiplicando nas células do fígado antes de explodir no sistema circulatório para devorar repetidamente o conteúdo dos glóbulos vermelhos como combustível para multiplicar.
O parasita também é geneticamente complexo, apresentando centenas de proteínas que se acredita serem dedicadas à evasão imune. As proteínas do parasita também apresentam um grande número de sequências repetidas simples que confundem os cientistas há décadas.
Diante de um inimigo tão sofisticado, talvez não seja surpreendente que tanto nossas respostas imunes naturais quanto os esforços para criar uma vacina sejam insuficientes. Somente com muitas exposições repetidas ao longo de suas vidas é que as pessoas nas regiões de transmissão da malária param de adoecer quando infectadas com o parasita - e às vezes nem isso é suficiente.
O longo período de tempo para desenvolver imunidade deixa as crianças particularmente em risco. Além do mais, a imunidade conquistada com muito esforço diminui rapidamente - as pessoas que saem de áreas de alta transmissão provavelmente perderão sua proteção e ficarão doentes novamente quando retornarem.
Esses desafios para desenvolver a imunidade natural foram transferidos para os esforços de vacinas. A vacina conhecida como RTS,S, a primeira a ser aprovada para a malária, requer uma série de quatro injeções e ainda tem apenas cerca de 30% de eficácia contra doenças graves, e a proteção que confere diminui após alguns meses.
"Há muita coisa que simplesmente não sabemos sobre como a imunidade à malária se desenvolve", disse Bryan Greenhouse, professor de medicina da UCSF e co-autor sênior do novo artigo. "Isso se deve em grande parte à falta de ferramentas para caracterizar de forma abrangente a resposta do sistema imunológico. Os novos métodos que desenvolvemos aqui, no entanto, ajudarão a fechar essa lacuna".
Três estágios diferentes do ciclo de vida do parasita da malária são mostrados nesta imagem capturada pelo microscópio de malária personalizado da CZ Biohub (agora sendo testado em campo em Uganda): caixas amarelas são parasitas em estágio de anel, rosa é um parasita em estágio de trofozoíto e laranja é um estágio esquizonte. As caixas verdes mostram células saudáveis. Crédito: CZ Biohub SF Plataforma de Bioengenharia
Mapeamento da resposta imune
Para entender melhor por que é tão difícil desenvolver imunidade contra a malária, os pesquisadores do Biohub SF e da UCSF utilizaram uma poderosa tecnologia chamada PhIP-Seq, que lhes permitiu analisar em laboratório como o sistema imunológico de pessoas expostas ao P. falciparum reagiu a ele .
A abordagem envolveu pegar todas as cerca de 5.400 proteínas que compõem o parasita P. falciparum - o "proteoma" do parasita - e cortá-las em centenas de milhares de pedaços, aproximando a escala em que nosso sistema imunológico funciona ao caçar pedaços de patógenos para alvo. Os pesquisadores então projetaram vírus para exibir cada um desses pequenos pedaços – como soldados agitando a bandeira de um exército inimigo – e os misturaram em pratos de laboratório com o sangue dos participantes do estudo.
"O que fizemos foi criar uma biblioteca de todos os componentes de todas as proteínas que a malária pode mostrar ao nosso sistema imunológico", disse DeRisi, também professor de bioquímica e biofísica na UCSF. “Podemos ver exatamente o que nosso sistema imunológico vê e tentar descobrir como ele está respondendo”.
Agora os pesquisadores puderam analisar quais pedaços do parasita acionaram anticorpos no sangue humano para combater a doença. Se o sistema imunológico encontrou um pedaço antes e produziu anticorpos, então os anticorpos devem mostrar reatividade a esses pedaços na plataforma PhIP-seq.
Como esperado, as amostras coletadas de um grupo de controle de adultos americanos, que, em sua maioria, provavelmente nunca foram expostos à malária, mostraram muito pouca reatividade aos fragmentos de proteína do parasita. Mas quando a equipe analisou o sangue doado por ugandenses, eles observaram padrões interessantes.
O sangue dos ugandenses continha anticorpos para muitos componentes do parasita da malária , mas mais comumente para pedaços de proteína apelidados de "elementos repetidos". Elementos repetidos são áreas de uma proteína onde as sequências de aminoácidos que a compõem se repetem continuamente e são consideradas de pouca utilidade na função da proteína.
Curiosamente, a resposta aos elementos repetidos dependia muito da exposição. Crianças ugandenses que vivem com exposição extremamente alta à malária – uma média de 49 vezes por ano através de picadas de mosquitos infectados – mostraram cerca de duas vezes mais reatividade a muitos desses elementos repetidos do que crianças que viviam em áreas de exposição moderada – cinco picadas infectadas por ano.
Mas a reatividade a alguns desses elementos repetidos diminuiu com o tempo mais do que a reatividade a regiões não repetidas. A grande diferença sugere que, embora os anticorpos para esses elementos repetidos dominem a resposta imune à malária, essa resposta é passageira e pode desaparecer mais rapidamente do que as respostas a regiões não repetidas.
“Essas repetições não tendem a ser alvos muito bons quando se trata de criar uma defesa de longo prazo”, disse Madhura Raghavan, bolsista de pós-doutorado em bioquímica e biofísica na UCSF e principal autora do novo estudo. “Os recursos imunológicos são limitados e, no caso da malária, nossos corpos parecem estar cometendo um grande erro de cálculo sobre o que eles visam para criar imunidade natural”.
DeRisi concordou, acrescentando: "Nosso sistema imunológico entra em ação para lidar com essas iscas. É uma distração tão grande que o corpo perde a oportunidade de desenvolver uma defesa que seria realmente útil na próxima vez."
As descobertas provavelmente representam uma lição importante para o desenvolvimento de vacinas, que normalmente se baseia em imitar a própria defesa imunológica do corpo, sem necessariamente avaliar sua eficácia. De fato, a vacina RTS,S usa um elemento de repetição do P. falciparum como alvo – uma possível explicação para sua baixa durabilidade.
Armados com sua nova biblioteca do proteoma P. falciparum, os pesquisadores da Biohub planejam continuar testando as respostas imunes à malária em Uganda, observando a seguir como essas respostas mudam ao longo do tempo e com diferentes níveis de exposição. Dados adicionais, eles esperam, acabarão por orientá-los para componentes específicos das proteínas do parasita que podem ser a chave para desencadear uma resposta imune mais eficaz por meio da vacinação.
"Infelizmente, a malária é simplesmente uma parte normal da vida cotidiana de muitas pessoas e a imunidade é a única coisa que as impede de ficar continuamente doentes ou morrer", disse Greenhouse. “É fundamental que continuemos trabalhando para entender melhor essa imunidade se quisermos ter a chance de desenvolver uma vacina eficaz que salva vidas”.
Mais informações: Madhura Raghavan et al, Anticorpos para antígenos contendo repetições em Plasmodium falciparum são dependentes de exposição e de curta duração em crianças com infecções naturais por malária, eLife (2023). DOI: 10.7554/eLife.81401
Informações do jornal: eLife