Os cientistas agora podem colher conteaºdos de células individuais de seu ambiente local
A nova ferramenta permitira¡ um estudo mais profundo de células-tronco e outros tipos de células raros para o desenvolvimento de terapia.
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)
Um chip microfluadico com gotas individuais mostradas em cores diferentes. Cada gota contanãm material de uma única canãlula e o entrega para análises a´micas de uma única canãlula. Crédito: Wheeler lab
Os cientistas agora podem selecionar células individuais de uma população que cresce nasuperfÍcie de uma placa de laboratório e estudar seu conteaºdo molecular. Desenvolvida por pesquisadores da Universidade de Toronto, a nova ferramenta permitira¡ um estudo mais profundo de células-tronco e outros tipos de células raros para o desenvolvimento de terapia.
O manãtodo éo primeiro a casar a microscopia celular com as plataformas a´micas para vincular a sua composição molecular os parametros fasicos das células visaveis a olho nu, como a aparaªncia, a presença de marcadores desuperfÍcie ou contatos canãlula-canãlula .
"Damos ao usua¡rio o poder de obter belas imagens de microscopia de fluorescaªncia para aprender tudo o que pode ser aprendido sobre o crescimento de células in situ e, em seguida, conectar essas informações com o genoma, transcriptoma e proteoma da canãlula", diz Aaron Wheeler, professor de química e biomédica engenheiros do Donnelly Center for Cellular and Biomolecular Research, que liderou o trabalho.
A plataforma édescrita em um artigo publicado hoje na revista Nature Communications .
Batizado de DISCO, de Isolamento microfluadico digital de células individuais para -Omics, o manãtodo permite aos pesquisadores selecionar células únicas em seu ambiente local e analisar seu conteaºdo com as tecnologias de sequenciamento de DNA e proteanas para ler o DNA da canãlula (genoma), o RNA dos genes transcritos (transcriptoma) e moléculas de proteana (proteoma).
O aumento das análises de uma única canãlula nos últimos cinco anos permitiu aos pesquisadores medir dezenas de milhares de moléculas em cada canãlula, transformando sua capacidade de estudar tecidos e órgãos em umnívelgranular. Mas essas abordagens perdem informações importantes sobre as caracteristicas físicas das células e o ambiente local porque as células devem ser colocadas em suspensão e separadas umas das outras antes da análise.
"Nossa plataforma se concentra nos metadados que vocêperde quando faz a suspensão de uma única canãlula, coisas como a posição da canãlula, quais eram suas propriedades morfola³gicas, quem eram seus vizinhos? Essas são todas as coisas que podemos capturar antes de fazer o sequenciamento de uma única canãlula, "
Erica Scott
"Ha¡ uma revolução acontecendo agora com a´micas de canãlula única", disse Wheeler, que éo Canada¡ Research Chair in Microfluidic Bioanalysis. "Mas eu encontrei pessoas que ficaram desapontadas porque não foram capazes de capturar informações fenotipicas sobre a canãlula em seu ambiente in situ."
"E eu pensei que poderaamos encontrar uma maneira de selecionar células especaficas dessa população e analisa¡-las", diz ele.
O DISCO écomposto por um microsca³pio equipado com um laser de alta frequência e um chip microfluadico para coleta de material celular. O microsca³pio permite ao usua¡rio obter imagens detalhadas da canãlula-alvo antes de direcionar o laser sobre ela. A energia do laser faz com que uma pequena bolha se forme e estale na proximidade da canãlula, rompendo sua membrana e lana§ando seu conteaºdo em uma gota no chip microfluadico, de onde érecuperado para sequenciamento molecular.
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"Nossa plataforma se concentra nos metadados que vocêperde quando faz a suspensão de uma única canãlula, coisas como a posição da canãlula, quais eram suas propriedades morfola³gicas, quem eram seus vizinhos? Essas são todas as coisas que podemos capturar antes de fazer o sequenciamento de uma única canãlula, "diz Erica Scott, um pa³s-doutorado no laboratório que liderou o trabalho junto com dois Ph.D. alunos do laboratório, Julian Lamanna e Harrison Edwards.
“Atéonde sabemos, esta éa única plataforma que pode levar células em cultura e fazer esse tipo de coisaâ€, diz ela.
Em experimentos de prova de princapio, os pesquisadores demonstraram a capacidade do DISCO de relacionar fielmente os dados a´micos a células cancerosas do cérebro de humanos e ratos individuais que foram cultivadas lado a lado.
Mas as descobertas também evidenciaram a extensão em que os contatos entre as células podem influenciar seus estados moleculares. A expressão de impressionantes 5.000 genes de camundongo - cerca de um quinto do genoma - foi alterada em células individuais de camundongo que haviam sido cercadas por células humanas em vez de seus pra³prios parentes.
As descobertas podem ter implicações importantes para muitos laboratórios que buscam obter uma melhor compreensão do tecido humano sauda¡vel e doente, como tumores, cultivando-os em camundongos para que possam ser estudados em um ambiente de corpo inteiro. Se a expressão do gene for afetada de forma semelhante no enxerto humano, essasmudanças podem ter ramificações para o desenvolvimento do tratamento, disse Wheeler.
Felizmente, o DISCO pode em breve oferecer uma janela para as células em seu ambiente natural, enquanto os pesquisadores estãotrabalhando para adapta¡-lo a análise de fatias de tecido. Seu objetivo final éaplicar DISCO ao estudo de tipos de células raros, como células- tronco , cujo potencial regenerativo éem grande parte regulado por seu ambiente imediato, para ajudar no avanço de novas terapias.