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UNIVERSIDADE ESTADUAL DE CAMPINAS
FACULDADE DE CIÊNCIAS MÉDICAS
Carlos Fernando Odir Rodrigues Melo
“ABORDAGEM LIPIDÔMICA PARA CARACTERIZAÇÃO DE CÉLULAS DE MOSQUITO INFECTADAS COM ZIKA VÍRUS:
POTENCIAIS ALVOS PARA A QUEBRA DO CICLO DE TRANSMISSÃO”
“A LIPIDOMICS APPROACH IN THE CHARACTERIZATION OF ZIKA-INFECTED MOSQUITO CELLS: POTENTIAL
TARGETS FOR BREAKING THE TRANSMISSION CYCLE”
CAMPINAS 2016
Carlos Fernando Odir Rodrigues Melo
“ABORDAGEM LIPIDÔMICA PARA CARACTERIZAÇÃO DE CÉLULAS DE
MOSQUITO INFECTADAS COM ZIKA VÍRUS: POTENCIAIS ALVOS PARA A
QUEBRA DO CICLO DE TRANSMISSÃO”
“A LIPIDOMICS APPROACH IN THE CHARACTERIZATION OF ZIKA-
INFECTED MOSQUITO CELLS: POTENTIAL TARGETS FOR BREAKING
THE TRANSMISSION CYCLE”
ORIENTADOR: PROF. DR. RODRIGO RAMOS CATHARINO
CAMPINAS
2016
Dissertação apresentada à Faculdade de Ciências Médicas da Universidade Estadual de Campinas como parte dos requisitos exigidos para a obtenção do título de Mestre em Ciências.
Dissertation submitted to the State University of Campinas School of Medical Sciences as part of the requirements for obtaining the title of Master of Science.
ESTE EXEMPLAR CORRESPONDE À VERSÃO FINAL DA DISSERTAÇÃO DEFENDIDA PELO ALUNO CARLOS FERNANDO ODIR RODRIGUES MELO, E ORIENTADO PELO PROF. DR. RODRIGO RAMOS CATHARINO.
BANCA EXAMINADORA DA DEFESA DE MESTRADO
CARLOS FERNANDO ODIR RODRIGUES MELO
ORIENTADOR: PROF. DR. RODRIGO RAMOS CATHARINO
MEMBROS:
1. PROF. DR. RODRIGO RAMOS CATHARINO
2. PROFA. DRA. DAISY MACHADO
3. PROFA. DRA. PATRICIA MARIA DE CARVALHO
Programa de Pós-Graduação em Fisiopatologia Médica da Faculdade de Ciências
Médicas da Universidade Estadual de Campinas.
A ata de defesa com as respectivas assinaturas dos membros da banca
examinadora encontra-se no processo de vida acadêmica do aluno.
Data: 01/08/2016
DEDICATORIA
Dedico este trabalho a minha família, em especial ao meu pai, por todo o amor,
apoio e confiança em mim depositados.
AGRADECIMENTOS
Primeiro aos meus pais, José Francisco de Melo e Maria Dulce Rodrigues
Melo, pois sem o esforço de vocês eu não teria chegado até aqui. Por causa de
tudo que fizeram que eu me tornei a pessoa que sou hoje. Obrigada por todo
apoio e incentivo, por todo amor, carinho, erros e acertos, pela confiança em
mim deposita.
À minha namorada, Tatiane, por todo amor, carinho, apoio e confiança.
Obrigada por sempre estar ao meu lado, pelo enorme companheirismo e força.
Aos meus amigos do Laboratório Innovare: Diogo, Cibele, Gustavo, Estela e
Maico. Obrigada por toda a ajuda que vocês me deram, paciência com a minha
falta de paciência e personalidade nem sempre amistosa.
Obrigado as alunas de iniciação científica, Aline Amorim e Carolina Tieme, por
sempre se predisporem a ajudar e o fazem da melhor maneira possível.
E por fim, ao meu orientador e amigo Prof. Dr. Rodrigo Ramos Catharino, por
todas as nossas conversas e orientações, tanto pessoais quanto profissionais.
Obrigada por sempre estar disposto à ajudar e a confiar no meu trabalho mais
que eu mesmo.
Muito obrigado!
RESUMO
Os recentes surtos de vírus Zika na Oceania e na América Latina
acompanhados por complicações clínicas inesperadas tornou esta infecção
uma preocupação de saúde pública global. Este vírus apresenta tropismo pelo
tecido neural e está associado à microcefalia em recém-nascidos de mães
infectadas. A relevância clínica desta infecção, a dificuldade de realizar um
diagnóstico preciso e a pequena quantidade de dados na literatura destaca a
necessidade urgente de estudos sobre a infecção por Zika vírus. A análise do
processo de infecção em células é essencial para a caracterização de novos
biomarcadores e para o estabelecimento de novas metas para o controle viral
no hospedeiro, seja ele vertebrado ou invertebrado. Assim, este estudo tem por
objetivo estabelecer um perfil lipidômico de células de mosquitos infectados e
não infectados, visando a definição de potencias alvos para o controle viral em
mosquitos. Ao todo foram identificados treze lipídeos potenciais marcadores
específicos para infecção por Zika vírus, esses podem se relacionados com o
mecanismo intracelular de replicação viral e/ou de reconhecimento celular.
Nossos achados bioquímicos podem traduzir-se em alvos úteis para quebrar o
ciclo de transmissão viral.
PALAVRAS CHAVE: Zika vírus, Lipidômica, Espectrometria de massas
ABSTRACT
The recent outbreaks of Zika virus in Oceania and Latin America accompanied
by unexpected clinical complications made this infection a global public health
concern. This virus has tropism to neural tissue, leading to microcephaly in
newborns from a significant proportion of infected mothers. The clinical
relevance of this infection, the difficulty to perform accurate diagnosis and the
small amount of data in literature highlights the urgent need for studies on Zika
infection. This is essential to the characterization of new biomarkers of this
infection and to the establishment of new targets for viral control in vertebrates
and invertebrate hosts. Thus, this study aims at establishing a lipidomics profile
of infected versus uninfected mosquito cells to define potential targets for viral
control in mosquitoes. We identified thirteen lipids that can be specific markers
for Zika virus infection, which were putatively linked to the intracellular
mechanism of viral replication and/or cell recognition. Our biochemical findings
may translate into useful targets for breaking the transmission cycle.
KEYWORDS: Zika virus, Lipidomic, Mass spectrometry
LISTA DE ILUSTRAÇÕES
FIGURA 1:DIFERENTE NÍVEIS DAS “ÔMICAS” DEMONSTRADOS COMO UMA
CASCATA QUE RELACIONA O GENÓTIPO COM O FENÓTIPO...................... .16
FIGURA 2:PRINCIPAIS CLASSES DE LIPÍDIOA: GLICEROLIPIDIOS,
ESFINGOLIPIDOS E ESTERÓIS; MOSTRADOS COM SUAS CABEÇAS
POLARES À DIREITA. OS ACILOS SÃO APRESENTADOS EM CAIXAS
CINZENTAS. OS PRINCIPAIS GLICEROLIPIDIOS SÃO MONTADOS POR
ESTERIFICAÇÃO DE ACILOS NAS POSIÇÕES SN-1 E SN-2 DA CADEIA DE
GLICEROL E UMA CABEÇA POLAR NA POSIÇÃO SN-3. EM ALGUNS CASOS,
AS CADEIAS DE ÁCIDOS GRAXOS
PODEM SER LIGADAS ATRAVÉS DE LIGAÇÕES ÉTER OU ÉTER DE VINILO.
OS ESFINGOLIPIDIOS SÃO MONTADAS POR LIGAÇÃO DE UM ÁCIDO GRAXO
ATRAVÉS DE UMA LIGAÇÃO AMIDA EM UMA BASE DE CADEIA LONGA,
TAMBÉM CHAMADA BASE ESFINGOIDE, TAL COMO A ESFINGOSINA. PA:
ÁCIDO FOSFATÍDICO; CDP-DAG: DIACILGLICEROL
CITIDINA DIFOSFATO; DAG: DIACILGLICEROL; PC: FOSFATIDILCOLINA; PE:
FOSFATIDILETANOLAMINA; PS:FOSFATIDILSERINA; PI:
FOSFATIDILINOSITOL; PG: FOSFATIDILGLICEROL;
DPG:DIFOSFATIDILGLICEROL (ADAPTADO DE MARÉCHAL ET. AL. 2011) ... 18
FIGURA 3: SCORES PLOT BETWEEN THE FIRST TWO PRINCIPAL COMPONENTS
(PCS) SELECTED. THE EXPLAINED VARIANCES ARE 33.5% FOR
COMPONENT 1 AND 52.5% FOR COMPONENT TWO ...................................... 29
FIGURA 4: CLUSTERING RESULT FOR THE 65 TOP FEATURES IN THE PLS-DA
VIP SCORES, SHOWN AS A HEAT MAP (DISTANCE MEASURED BY
EUCLIDEAN AND CLUSTERING ALGORITHM USING WARD.D) ..................... 30
FIGURA 5: SEMIQUANTITATIVE ANALYSIS OF CHARACTERISTIC LIPIDS
SHOWED THAT ZIKV- INFECTED CELLS. THE BARS REPRESENTING
CONFIDENCE INTERVAL OF 95% (**** P<0.0001) ............................................ 33
FIGURA 6: CHEMICAL IMAGES FROM MALDI-MSI SHOWING THE
COMPARISON BETWEEN INFECTED AND UNINFECTED CELLS. IT IS
VISUALLY POSSIBLE TO ASSESS THE DIFFERENCE IN LIPID
COMPOSITION OF ZIKV-SPECIFIC CHARACTERIZED BIOMARKERS.
........................................................................................................................... 35
LISTA DE TABELAS
TABELA 1:LIPIDS MARKERS ELECTED BY PLS-DA VIP SCORES ≥ 1.5 AND ELUCIDATED BY MS/MS FOR AEDES ALBOPICTUS C6/36 INFECTED CELLS (ZIKV ROUP)………………………………………………………………………… 27
TABELA 2:LIPIDS MARKERS ELECT BY PLD-DA VIP SCORE ≥ 1.5 AND
ELUCIDATED BY MS/MS FOR AEDES ALBOPICTUS C6/36 UNINFECTED CELLS (CONTROL GROUP)………………………………………………………………………………..28
LISTA DAS ABREVIATURAS
ZIKV Zika Vírus
DENV Vírus da Dengue
CHIV Vírus Chicungunha
OROV Vírus OropoUche
MAC – ELISA IgM Antibody-Capture Enzyme-Linked
Immunosorbent Assay
RT-PCR Reverse Transcription Polymerase Chain Reaction
RNA Ribonucleic Acid
DNA Deoxyribonucleic Acid
EM Espectrometria de Massas
CCD Cromatografia em Camada Delgada
CL Cromatografia Líquida
EFS Extração em Fase Sólida
CLAE Cromatografia Liquida de Alta Eficiência
CG Cromatografia Gasosa
MALDI Matrix-Assisted Laser Desorption Ionization
ESI Electrospray Ionization
APCI Atmospheric Pressure Chemical Ionization
IV Infravermelho
UV Ultravioleta
IMS Imaging Mass Spectrometry
VRC Viral replication complexes
PC Phosphatidylcholine
LD Lipid Droplets
PLS-DA Partial Least Squares – Discriminant Analysis
VIP Variable Importance in Projection
MS/MS Espectrometria de massas em modo tandem
PS Phosphatidylserines
PE Phosphatidylethanolamines
PA Phosphatidic Acid
TG Triacylglycerol
SL Sphingolipids
Sumário
Introdução .................................................................................................... 13
Vírus Zika .................................................................................................. 13
Aedes Aegypti ........................................................................................... 14
Metabolômica ............................................................................................ 15
Lipídeos e Lipidômica Lipídeos ................................................................. 16
Lipidômica ................................................................................................. 17
Análise de lipídeos e Espectrometria de Massas (EM) ............................. 19
Análise por Matrix-Assisted Laser Desorption Ionization - Imaging Mass Spectrometry (MALDI-IMS) .......................................................................... 20
Objetivos ...................................................................................................... 22
Objetivo Geral ........................................................................................... 22
Objetivos Específicos ................................................................................ 22
CAPÍTULO I ................................................................................................. 23
A Lipidomics Approach in the Characterization of Zika-infected Mosquito Cells: Potential Targets for Breaking the Transmission Cycle ..................... 24
Introduction ............................................................................................... 25
Results ...................................................................................................... 26
Discussion ................................................................................................. 31
Acknowledgements ................................................................................... 37
Methods .................................................................................................... 37
Competing financial interests .................................................................... 40
Referências da introdução ........................................................................... 43
13
Introdução
Vírus Zika
O Zika vírus (ZIKV) é um arbovírus da família Flaviviridae que foi isolado pela
primeira vez em macacos da floresta de Zika, em Uganda no continente Africado1,
onde seu vetor é o mosquito Aedes africanos2. A despeito do macaco ser seu
reservatório natural a contaminação de humanos com o vírus foi verificada
posteriormente3, ocorrendo relatos de surtos urbanos da infecção por ZIKV. Estes
surtos eram relatos isolados e extremante pontuais em uma determinada localidade
geográfica, como os que ocorreram na Nigéria em 19524 ou na Indonésia e, 19785.
Recentemente, mais especificamente de 2013 em diante, o ZIKV tem preocupado as
autoridades sanitárias em razão de estar se propagando muito rapidamente e com
presença já confirmada em 33 países do continente americano, sobretudo nos países
localizados na região equatorial3, mesma latitude em que se encontram os países do
sudeste asiático com incidência desta infecção6.
No continente africano, esta então zoonose, era transmitida pelo mosquito A.
africanos e a hipótese que explica a razão pela qual esse vírus passou a ser cada vez
mais encontrado em humanos é devido às alterações climáticas e ao rápido tráfego de
pessoas pelo mundo; pois através dos atuais meios de transporte, o vírus, que até
então estava restrito à uma região do continente africano e a um vetor específico,
conseguiu chegar a outras localidades e a se adaptar ao homem e a outros vetores
urbanos como o A. aegypti e A. albopictus7, estabelecendo-se desta forma um novo
ciclo na infecção do homem pelo ZIKV, onde não envolveria a relação animal-
artrópode-homem, mas sim homem-artrópode-homem. Estes novos vetores
encontrados pelo ZIKV se caracterizam por possuir alta capacidade vetorial, ou seja,
apresentam alta capacidade de transmitir um agente patogênico num determinado
local e a um tempo específico. As fêmeas do A. aegypti, principal vetor do ZIKV em
regiões urbanas, têm como característica se alimentarem principalmente de sangue de
seres humanos e frequentemente conseguem morder vários indivíduos em um único
período de alimentação, sendo a sua picada quase imperceptível. O A. aegypit vive
em estreita associação com a habitação humana, desta forma, o ZIKV ao estabelecer-
se neste novo vetor, promoveu o aumento exponencial de casos de infecção8 e tornou-
se um vírus urbano.
As manifestações clínicas da infecção por ZIKV não são nada específicas de
maneira que o diagnóstico clínico pode ser confundido com infecção pelo vírus da
dengue (DENV), Chikungunia (CHIV) ou até mesmo Oropoche (OROV), já que os
14
sintomas mais frequentemente são os mesmos: exantema macular ou papular, febre,
artrite ou artralgia, conjuntivite não purulenta, mialgia, cefaléia, febre, dor retro-orbital,
edema e vômitos9. Os diagnósticos laboratoriais existentes hoje em dia também
apresentam dificuldades na sua realização uma vez que o exame sorológico, que visa
a detecção de anticorpos IgM por meio de ensaio imunossorvente ligado a enzima
(MAC - ELISA do inglês IgM antibody-capture enzyme-linked immunosorbent assay)
apresenta reação cruzada com outros tipos de Flavivírus como o DENV, não sendo o
resultado conclusivo10 já ao exame virológico, que é considerado padrão ouro para o
diagnóstico feito por meio de Reação em Cadeia da Polimerase de Transcriptase
Reversa (RT-PCR do inglês Reverse transcription polymerase chain reaction) é
possível fazer apenas na fase aguda da doença, sendo os melhores resultados
obtidos em pacientes que realizaram o exame após uma semana do início das
manifestações clínicas, essa dificuldade se dá uma vez que a viremia do ZIKV é baixa,
tornando o isolamento do vírus a partir de amostras clínicas extremante difícil11.
A infecção pelo ZIKV é quase sempre autolimitada e subdiagnósticada, mas
com o recente surto de ZIKV, tem-se observado um aumento na síndrome de Guillain–
Barré que se caracteriza como uma doença autoimune que causa paralisia flácida
aguda ou subaguda e ao aumento no nascimento de bebês microcefálicos a partir de
mães infectadas com ZIKV12. Esta última é uma condição neurológica rara em que a
cabeça e o cérebro da criança são significativamente menores do que os de outras da
mesma idade e sexo, devido ao cérebro não crescer o suficiente durante a gestação
ou após o nascimento, o que acarreta inúmeros problemas relacionados ao
desenvolvimento neurológico13.
Aedes Aegypti
O Aedes aegypti é um mosquito originário do Egito e foi descrito cientificamente
pela primeira vez em 1762, sendo inicialmente denominado Cúlex aegypti (Cúlex
significa “mosquito” e aegypti, egípcio) já que o gênero Aedes só foi descrito em 1818,
e em seguida se verificou que a espécie aegypti, já descrita, apresentava
características morfológicas e biológicas semelhantes às de espécies do gênero
Aedes, fato que alterou a classificação desse mosquito de Cúlex para Aedes, sendo
então estabelecido: Aedes aegypti14,15. Estes mosquitos saíram do continente africano
principalmente a partir dos navio negreiros que faziam tráfico de escravos da África
para Europa e América16,17,18.
Os mosquitos fêmea mordem animais dado a necessidade de sangue para a
maturação dos ovos e neste processo, se o animal mordido estiver infectado com o
15
ZIKV, ao ingerir o sangue o mosquito se infectada com o vírus e passa então a ser um
vetor para o ZIKV. O vírus se instala nas glândulas salivares do mosquito e o morder
um animal para sugar o sangue o mosquito injeta inicialmente saliva no local da
mordida com o intuito de não deixar o sangue coagular e o animal não sentir dor,
entretanto quando a saliva do mosquito esta infectada o ZIKV, este entra em contato
com a corrente sanguínea do animal, que passa agora estar infectado pelo ZIKV. De
uma maneira geral, os mosquitos têm por hábito sugar o sangue de uma só
pessoa/animal a cada ovo postura, entretanto o A. aegypti é capaz de morder mais de
uma pessoa/animal a cada ovo postura, processo que é chamado de discordância
gonotrófica, tornando-o um excelente vetor para doenças pois há um grande número
de pessoas diferentes que o mosquito é capaz de morder e consequentemente
transmitir o vírus, caso esteja infectado18. A maneira como o vírus é combatido pelo
mosquito ainda é muito pouco explorada, sendo normalmente abordados modelos de
estudo já estabelecido com a Drosófila melanogáster19, adicionalmente os estudos
focam genômica e proteômica19,20,21,22,23 não tendo estudos que analisam o fenótipo
metabolômico relacionado ao mecanismo de infecção viral no mosquito.
Metabolômica
Hoje o grande desafio dos pesquisadores não é mais desvendar as sequências de
pares de bases nitrogenadas que compõe o RNA de um vírus ou o DNA de um animal
qualquer, haja visto a grande quantidade de genomas disponíveis em domínio público.
O desafio agora é o de conectar os genes com suas funções, relacionar o genótipo
com o fenótipo. O impulso para entender a função dos genes descobertos
recentemente alavancou a análise sistemática dos níveis de expressão de
componentes de um sistema biológico, tais como mRNA, proteínas e metabólitos, e a
catalogação global destes componentes tem dado origem a vários “OMAs” (o genoma,
o proteoma, o metaboloma). Entender a rede de componentes e como eles interagem
é a base do acesso aos sistemas biológicos24.
A Metabolômica é o estudo sistemático e completo da série de intermediários de
baixo peso molecular, não protéicos, sintetizados endogenamente (o metaboloma) e
que esteja contido em uma célula representando o produto final da expressão gênica.
Dentre esses estão os aminoácidos, ácidos nucléicos, açúcares e lipídeos. Assim, a
partir da metabolômica surgiram subáreas dentre elas a glicômica e a lipidômica24, 35. A
Figura 1 mostra como a lipidômica, por meio da metabolômica, representa o ponto
final da cascata “ÔMICA” e consequentemente o ponto mais próximo ao fenótipo.
Assim a lipidômica, como a metabolômica, se desenvolve como uma ferramenta
16
funcional da genômica. Combinando a genômica, transcriptômica, proteômica e a
metabolômica (lipidômica), essas podem fornecer uma poderosa série de ferramentas
para examinar mudanças fenotípicas35.
Figura 1:Diferente níveis das “ÔMICAS” demonstrados como uma cascata que relaciona o genótipo com
o fenótipo35
.
Uma vez que o vírus depende exclusivamente do metabolismo celular da célula
hospedeira para sua replicação, no processo de infecção celular; ele altera a
metabolômica celular a fim que a célula produza os metabólitos necessários para sua
infecção e replicação36. A partir das alterações fenotípica apresentadas pelas células
infectadas é possível verificar quais vias metabólicas estão ativas ou têm sua atividade
aumentada, ajudando a entender como se dá o processo de infecção celular pelo vírus
37,38, 39, 36.
Lipídeos e Lipidômica
Lipídeos
Lipídeos podem ser definidos, de uma maneira geral, como pequenas
moléculas hidrofóbicas ou anfifílicas que podem se originar parcial ou inteiramente
pela condensação de subunidades de cetoacil e isoprenos, oleosos ao toque, e que,
juntamente com carboidratos e proteínas, constituem o principal material estrutural
para a vida celular34,40,41,42,43.
17
A maioria dos lipídeos que ocorrem biologicamente são combinações lineares
de cadeias alifáticas e grupos com cabeças polares ligados glicerol ou esfingolipídeos,
assim como cadeias alifáticas covalentes ligadas a colesterol. A grande variabilidade
de lipídeos ocorre em razão à grande variabilidade estrutural que pode ocorrer nas
combinações como demonstrado na figura 2, dentre elas: natureza dos grupos da
cabeça (definindo classes lipídicas); tamanho das cadeias alifáticas; número, posição
e estereoquímica de duplas ligações; grupos hidroxil e outras funções nas cadeias
alifáticas; a natureza das ligações covalentes do grupo da cabeça (éter, éster, vinil
éster)41, 44.
Lipidômica
Os lipídeos apresentam ampla função dentro das células, incluindo constituinte
de membranas, manutenção de gradientes eletroquímicos, primeiros e segundos
mensageiros na sinalização celular, estoque de energia, transporte de proteínas e
ancoramento de membranas em gradientes eletroquímicos35,45,41,42,43.
A lipidômica, uma subclasse da metabolômica, que pode ser definida como a
determinação molecular, quantitativa e completa, de moléculas de lipídeos isolados a
partir de células, tecidos e fluidos biológicos, em várias condições fisiológicas e
patológicas34,35,40,46, existindo duas maneiras de se fazer estudos em lipidômica: com
alvo (Target Lipidomic) e sem alvo (Untarget Lipidomic). Na lipidômica com alvo os
lipídeos caracterizados e quantificados já são conhecidos e propostos no início do
estudo, já estudos de lipidômica sem alvo os lipídeos que serão caracterizados e
quantificados ainda são desconhecidos, sendo descobertos a partir dos dados
encontrados nos experimentos realizados34,35,40.
A lipidômica está se desenvolvendo rapidamente e emergindo como uma
disciplina independente de interface entre biologia lipídica, tecnologia e medicina. A
diversidade e complexidade dos lipidomas biológicos requerem inovações técnicas e
18
Figura 2:Principais classes de lipídioa: glicerolipidios, esfingolipidos e esteróis; mostrados com suas cabeças polares à direita. Os acilos são apresentados em caixas
cinzentas. Os fosfatos são apresentados comcírculos azuis. Os principais glicerolipidios são montados por esterificação de acilos nas posições sn-1 e sn-2 da cadeia de glicerol e uma cabeça polar na posição sn-3. Em alguns casos, as cadeias de ácidos graxos podem ser ligadas através de ligações éter ou éter de vinilo. Os esfingolipidios são montadas por ligação de um ácido graxo através de uma ligação amida em uma base de cadeia longa, também chamada base esfingoide, tal como a esfingosina. PA: Ácido fosfatídico; CDP-DAG: Diacilglicerol citidina difosfato; DAG: Diacilglicerol; PC: Fosfatidilcolina; PE: Fosfatidiletanolamina; PS:Fosfatidilserina; PI: Fosfatidilinositol; PG: Fosfatidilglicerol; DPG:Difosfatidilglicerol (adaptado de Maréchal et. al. 2011) .
19
melhoramento para suprir a necessidade dos vários estudos biomédicos
desenvolvidos. A recente onda de expansão no campo da lipidômica pode ser
atribuído a avanços na tecnologia analítica, em particular, o desenvolvimento de novas
ferramentas de cromatografia, espectrometria de massas e bioinformática para
quantificação e caracterização da grande série de lipídeos presentes em um lipidoma.
40, 47.
Uma uma vez que o vírus se utiliza da maquinaria celular no processo de
infecção e replicação, alguns desses lipídeos são cruciais também para o vírus38,39,
entretanto as informações de suas funções no processo de infecção viral, bem como
sua função estrutural nos vírus ainda muito pouco explorada sendo uma área quase
que desconhecida e que recentemente tem-se demonstrado de extrema importância
no processo de infecção e de manutenção da replicação viral37, 38, 39.
Análise de lipídeos e Espectrometria de Massas (EM)
Estratégias tradicionais de análise de lipídeos usualmente pré-fracionam os
lipídeos em classes por Cromatografia em Camada Delgada (CCD), Cromatografia
Líquida (CL) ou Extração em Fase Sólida (EFS), e depois separam as classes
particulares de lipídeos em moléculas individuais por Cromatografia Liquida de Alta
Eficiência (CLAE) acoplada a diferentes detectores. Com estes métodos tradicionais
as moléculas individuais de muitas classes de lipídeos podem ser analisadas, porém
estes apresentam baixa sensibilidade, resolução limitada, necessitam de grande
quantidade de amostra e muitas vezes são necessários vários passos para sua
preparação42,47.
Com o desenvolvimento de técnicas mais modernas como a CL e a Cromatografia
Gasosa (CG) a separação de muitos lipídeos de misturas simples se tornou possível.
No entanto, a identificação e quantificação de lipídeos em misturas complexas, tais
como extratos brutos de lipídeos, ainda permanece desafiador e muitos procedimentos
demorados, como hidrólise e derivatização, são utilizados para uma melhor resolução
dos lipídeos na separação por cromatografia.
A análise de lipídeos sofreu um grande avanço com a utilização da Espectrometria
de Massas (EM)42,44,46, principalmente com o desenvolvimento da tecnologia da
ionização suave tais como ionização por dessorção a laser assistida por matriz (Matrix-
Assisted Laser Desorption Ionization – MALDI), ionização por electrospray
(Electrospray Ionization - ESI), ionização química por pressão atmosférica
(Atmospheric Pressure Chemical Ionization – APCI), que tornaram possível em uma
20
única análise a avaliação rápida e sensível da maioria, ou fração substancial, dos
lipídeos presentes em uma matriz complexa34,44,46.
Comumente os lipídeos são extraídos antes de serem submetidos a análise por
EM por diferentes métodos de extração tais como Bligh Dyer48 e Folch49. Em um típico
experimento de lipidômica, a amostra lipídica é injetada no EM, ionizada e vaporizada,
resultando em íons que são separados de acordo com sua relação massa/carga (m/z)
no analisador de massas42. Existem duas ferramentas fundamentais para identificação
e quantificação de lipídeos por EM. O primeiro, e o mais tradicional, é o CLASS
(“Comprehensive Lipidomics Analisys by Separation Simplification”), baseado na
separação de diferentes categorias de lipídeos utilizando extração e separação
cromatográfica antes da análise de massas e depois otimização do espectrômetro de
massas para analisar classes específicas de lipídeos. A segunda ferramenta, também
chamada de Shotgun Lipidomics, omite a separação cromatográfica e analisa
essencialmente todas as classes de lipídeos, por injeção direta no espectrômetro de
massas enquanto emprega diferentes fontes de polaridade de íons (para formar íons
positivos e negativos) e adicionar soluções ionizantes para favorecer a análise de
classes específicas de lipídeos34,42. Neste estudo a segunda abordagem foi utilizada.
Análise por Matrix-Assisted Laser Desorption Ionization - Imaging Mass
Spectrometry (MALDI-IMS)
A técnica de ionização utilizada para a realização dos experimentos foi MALDI,
que se baseia na utilização de uma matriz composta de ácidos orgânicos de baixo
peso molecular para o recobrimento da amostra. Esse recobrimento é realizado
apergindo à solução de metanol:acetonitrila (1:1) contendo 10 µg de matriz sobre o
analito. Um feixe de laser (infravermelho – IV ou ultravioleta – UV) incide na amostra,
onde a matriz tem a função de absorver a energia do laser, aquecer e sofrer rápida
evaporação (sublimação), promovendo assim a ionização do analito. A ionização
ocorre devido as características químicas da matriz, através da doação ou retirada de
íons H+, gerando íons positivos do tipo [M + H]+ ou negativos do tipo [M – H]-. As
moléculas ionizadas e no estado gasoso são aceleradas pelo potencial elétrico
aplicado à sonda em direção ao analisador de massas e, posteriormente, detectadas
50,51.
MALDI-MSI permite a análise espacial da distribuição de metabólitos
diretamente em amostras biológicas, sem qualquer conhecimento prévio ou a
necessidade de reagentes específicos e embora possua algumas desvantagens em
termos de resolução espacial, MALDI é considerada a melhor técnica atualmente
21
disponível para imageamento de lipídeos, sendo uma técnica rápida e a partir das
imagens químicas é possível quantificar os analtos a partir da densidade de pixels52.
22
OBJETIVOS
Objetivo Geral
Determinar as alterações no lipidoma de células de mosquito infectadas com o Zika
vírus (ZIKV) utilizando técnicas baseadas em Espectrometria de Massas (EM).
Objetivos Específicos
- Determinar as alterações no lipidoma celular de céluals de mosquito C6/36 infectada
com ZIKV através de análise direta, utilizando uma nova metodologia baseada na EM;
- Quantificar as alterações no lipidoma celular de células de mosquito infectadas com
ZIKV quando comparadas com células de mosquito não infectadas por meio de
metodologia baseada no MALDI-IMS.
23
CAPÍTULO I
ABORDAGEM LIPIDÔMICA PARA
CARACTERIZAÇÃO DE CÉLULAS DE MOSQUITO INFECTADAS COM ZIKA
VÍRUS: POTENCIAIS ALVOS PARA A QUEBRA DO CICLO DE
TRANSMISSÃO
24
A Lipidomics Approach in the Characterization of Zika-infected Mosquito Cells:
Potential Targets for Breaking the Transmission Cycle
Carlos Fernando Odir Rodrigues Melo1, Diogo Noin de Oliveira1, Estela de Oliveira
Lima1, Tatiane Melina Guerreiro1, Cibele Zanardi Esteves1, Raissa Marques Beck3,
Marina Aiello Padilla3, Guilherme Paier Milanez2, Clarice Weis Arns3, José Luiz
Proenca-Modena2, Jayme A. Souza-Neto2,3 and Rodrigo Ramos Catharino1*
1 Innovare Biomarkers Laboratory, School of Pharmaceutical Sciences, University of
Campinas, 13083-877, Brazil.
2 Emerging viruses study Laboratory, Department of Genetics, Evolution and
Bioagents, Institute of Biology, University of Campinas, 13083-862, Brazil.
3 Animal viruses Laboratory, Department of Genetics, Evolution and Bioagents,
Institute of Biology, University of Campinas, 13083-862, Brazil.
4 Vector Functional Genomics & Microbiology Laboratory, UNESP Institute of
Biotechnology, São Paulo State University, Alameda das Tecomarias s/n, Botucatu,
18607-440, Brazil.
5 Department of Bioprocesses and Biotechnology, Faculty of Agronomical Sciences,
São Paulo State University, Rua José Barbosa 1780, Botucatu, 18610-307, Brazil. *Corresponding author (RRC): [email protected]
The recent outbreaks of Zika virus in Oceania and Latin America accompanied
by unexpected clinical complications made this infection a global public health
concern. This virus has tropism to neural tissue, leading to microcephaly in
newborns from a significant proportion of infected mothers. The clinical
relevance of this infection, the difficulty to perform accurate diagnosis and the
small amount of data in literature highlights the urgent need for studies on Zika
infection. This is essential to the characterization of new biomarkers of this
infection and to the establishment of new targets for viral control in vertebrates
and invertebrate hosts. Thus, this study aims at establishing a lipidomics profile
of infected versus uninfected mosquito cells to define potential targets for viral
25
control in mosquitoes. We identified thirteen lipids that can be specific markers
for Zika virus infection, which were putatively linked to the intracellular
mechanism of viral replication and/or cell recognition. Our biochemical findings
may translate into useful targets for breaking the transmission cycle.
Introduction
Zika virus (ZIKV) is an emerging arbovirus that is transmitted by mosquitoes of
the genus Aedes1, and was first isolated in 1947 in eastern Africa, remaining restricted
to the African and Asian continents until 2007, where it was seldom observed in
humans2. Typically, the infection of ZIKV in humans is asymptomatic or associated with
a self-limiting febrile illness in only 20% of infected people. However, recent outbreaks
of ZIKV in South Pacific and Latin America have evidenced the virus potential to cause
severe neurological damage-associated complications such as Guillain-Barré
syndrome3 and microcephaly in newborns4.
Similarly to dengue virus (DENV), ZIKV is an enveloped single-stranded
positive RNA virus whose 10.7-kb genome encodes three structural proteins (C,
capsid; M, membrane; and E, envelope) and seven nonstructural proteins (NS1, NS2a,
NS2b, NS3, NS4a, NS4b and NS5)2,5. The E protein is a major ZIKV antigen and
coordinates the association between the virion and the host’s viral receptors and
membrane lipids6,7. Recent studies have demonstrated that viral and host lipids play an
important role in the attachment process during viral infection. These lipids, adhered to
the capsid surface, coordinate viral recognition allowing its entry into the host cell8-13.
Intracellular host cell membranes multiply and reorganize during infection in
order to form viral replication complexes (VRCs), leading to the accumulation of
phosphatidylcholine (PC) in the VRCs as demonstrated for Poliovirus and Hepatitis C14.
Furthermore, VRC biogenesis requires increased membrane fluidity in order to facilitate
viral RNA transfer throughout pores formed on the packing vesicles14. Strikingly, a
recent lipidomics study has demonstrated that intracellular membrane alterations
26
induced by DENV are intimately associated with a set of lipids uniquely found on
DENV-infected mosquito cells, especially in association with VCR membranes15,
highlighting the crucial role of such molecules in this process.
On the other hand, lipid droplets (LDs) have been recently pointed out as an
important component of the A. aegypti antiviral defenses16, which also rely on the RNAi
machinery17 and innate immune pathways Toll and JAK-STAT18,19 to contain viral
replication. LDs accumulate upon bacterial and viral infections in both adult mosquito
midgut and cell lines, in a process that seems to be associated with the activation of
NF-k-B immune pathways, with the participation of the insect gut microbiota16.
While much progress has been achieved in the past decade towards
understanding the mosquito’s transcriptional and metabolic responses to DENV
infection, mosquito-ZIKV interactions continues largely unknown. In addition to the
limitations of both clinical and laboratory diagnosis and the absence of a specific
treatment for ZIKV infection2,20,21, this poses an important challenge for the
development of control interventions.
The present study aims at verifying the alterations in the mosquito cell lipidome
during ZIKV infection using the MALDI Mass Spectrometry Imaging (MALDI-MSI)
approach in order to identify and characterize important molecules associated with
Aedes-ZIKV interactions. Our findings indicate that Aedes’ cells increase their
glycerophospholipid metabolism for some lipids, in the same way as with DENV
infection15. These lipids may represent potential targets for blocking viral replication in
mosquitoes or for further developments in novel therapeutic approaches in humans,
since it is known that some factors required for viral infection are conserved among
Diptera and human hosts22.
Results
In order to analyze the main metabolites involved with ZIKV infection in the
mosquito, we performed a metabolomic analysis on both Aedes albopictus C6/36
27
infected and uninfected cells. Our data suggest that a large amount of lipids is involved
in the responses to ZIKV infection. A PLS-DA statistical analysis of our mass
spectrometry-derived data evidenced a clear separation between Zika-infected and
uninfected C6/36 mosquito control cells, as demonstrated in Figure 1. Using VIP
scores, 65 features were identified with a score value greater or equal to 1.5, as
demonstrated in Figure 2; the ZIKV-infected cells accounted for 37 characteristic
markers whereas the uninfected control ones displayed 28 molecules. Out of these 65
features, 20 lipid markers were identify using tandem mass spectrometry (MS/MS),
divided in 13 species for the ZIKV-infected group (Table 1) and 7 for the control group
(Table 2).
Table 1: Lipids markers elected by PLS-DA VIP scores ≥ 1.5 and elucidated by MS/MS for Aedes albopictus C6/36 infected cells (ZIKV group).
Class Ion (m/z)
Molécula MS/MS
Sphingolipid 400 Sphingofungin F 311, 336, 356
Phosphatidylserine
516 PS(18:4(6Z,9Z,12Z,15Z)/0:0) 272, 289, 326, 345
518 PS(18:3(9Z,12Z,15Z)/0:0) 373, 387, 429, 474
520 PS(18:2(9Z,12Z)/0:0) 375, 429, 431, 476
540
PS(20:6(2Z,5Z,8Z,11Z,14Z,17Z)/0:0) 373, 395, 400, 491, 496, 522
542 PS(20:5(5Z,8Z,11Z,14Z,17Z)/0:0) 375, 402, 493, 498
544 PS(20:4(5Z,8Z,11Z,14Z)/0:0) 355, 399, 456, 500
Phosphatidylcholine
530 PC(19:3(10Z,13Z,16Z)/0:0) 472, 512
536 PC(19:0/0:0) 311, 404, 445, 447
556
PC(6:2(3E,5E)/14:2(11E,13E)) 373, 389, 400, 416, 512
558
PC(6:2(3E,5E)/14:1(13E)) 375, 402, 412, 418, 514
Dyacylglicerole 563 DG(16:1(9Z)/16:1(9Z)/0:0) 519, 537, 545
Phosphatidylethanolamine 632 PE(12:0/16:1(9Z)) 544, 562, 588
28
Of the 13 lipids species indentified for ZIKV-infected cells, 12 participate directly
in the intracellular metabolism of glycerophospholipid in the host cells: 8 are
acylglycerophospholipids, divided into 6 acylglycerophosphoserines and 2
acylglycerophosphocholines; 3 species are diacylglycerophospholipids, divided in two
diacylglycerophosphocholines and 1 diacylglycerophosphoserine; 1 is a
diacylglycerol; and one is sphingolipid. Thus, these data suggest that the
glycerophospholipid metabolism pathway activity is much increased in the ZIKV-
infection group, similarly to other viral infections14,15,23.
Table 2: Lipids markers elect by PLD-DA VIP score ≥ 1.5 and elucidated by MS/MS for Aedes albopictus C6/36 uninfected cells (Control group).
Class Ion (m/z)
Molécula MS/MS
Phosphatidic Acid 409 PA(16:0/0:0) 263, 365, 391
Phosphoethanolamine
757 PE(18:2(9Z,12Z)/19:0) 713, 730, 739
773 PE(20:0/18:1(9Z)) 627, 645, 728, 755
779 PE(16:0/22:6(54Z,7Z,10Z,12E,16Z,19Z) (14OH))
502, 546, 589, 735
Phosphatidylserine
881 PS(22:4(7Z,10Z,13Z,16Z)/21:0) 736, 836, 863,
903 PS(22:0/22:0) 714, 758, 858, 884
Triacylglycerol 925 TG(18:2(9Z,12Z)/20:4(5Z,8Z,11Z,14Z)/ 20:4(5Z,8Z,11Z,14Z))
881, 899, 907
To corroborate the abovementioned evidence of ZIKV infection interference in
the metabolism pathway activity of mosquito cells, a semiquantitative analysis of
characteristic lipids showed that ZIKV-infected cells presented statistically significant
higher levels (p<0.05) of all PLS-DA-elected lipids as characteristic markers for ZIKV-
infection based on the quantitative comparison performed with each marker between
ZIKV-infection and control samples (Figure 3), evidencing a trend similar to that
obtained through PLS-DA analyses. Amounts up to 2.15-fold higher than those in the
control group are observed for some metabolites, as it is the case for the ion at m/z 556
[PC(6:2(3E,5E)/14:2(11E,13E))].
29
Figure 1: Scores plot between the first two principal components (PCs) selected. The
explained variances are 33.5% for component 1 and 52.5% for component two.
On the other hand, the quantitative comparison between the markers in
control and ZIKV-infected cells was not statistically significant, despite a slight
increase in the amount of elected markers in the control cells was observed
(p<0.05, data not shown), suggesting that the same lipids metabolized by the
glycerophospholipid metabolism on the control cell are metabolized on the
ZIKV-infection. This may be explained by the fact that both ZIKV-infected and
uninfected cells have essentially the same metabolic profile, except for some
specific metabolic changes induced by the virus in the cell line14,24; the regular
glycerophospholipid metabolism, however, remain at lower levels when the cell
is in homeostasis25. Figure 4 presents a comparison between the two groups,
where it is visually possible to assess the difference in lipid composition of
30
ZIKV-specific characterized biomarkers. Although this study uses mosquito
cells, the host factors here may be the same for the human, since some viral
host factors are the same for both human and mosquito cells22. The identified
lipid classes will be discussed in detail in the subsections below.
Figure 2: Clustering result for the 65 top features in the PLS-DA VIP scores, shown as
a heat map (distance measured by Euclidean and clustering algorithm using ward.D).
31
Discussion
Sphingolipids (SL)
Sphingofungin F, the ion at m/z 400 (Table 1), was the SL found as maker for
ZIKV infection, This compound was isolated for the first time during the fermentation of
Paecilomyces variotii (ATCC 74097), and it is a bioactive lipid that acts as the inhibitor
of serine palmitoyltransferase (SPT), an essential enzyme during the biosynthesis of
SL (26). The SPT inhibitor was initially investigated for its antifungal activity; however,
later studies showed that these inhibitors suppress viral replication, as described with
for myriocin-based SPT inhibition in hepatitis C virus (HCV)24,26, as well as for 4-
hydroxyphenyl retinamide inhibitor in a study with DENV27. Like ZIKV, these two
viruses also belong to the Flaviviridae family. No previous report has ever implicated
this SL as an insect metabolite; it has only been associated to fungi metabolism1. As
observed in Figure 4, this molecule is present in both cultures, but the relative amount
in the ZIKV-infected group is 1.64-fold (p<0.0001) higher than in the control group. This
may be an indicative that the infected cells are responding to viral infection, in an
attempt to impair viral replication.
Phosphatidylserines (PS)
PS is the most abundant anionic lipid class in the plasma membrane of
eukaryotes. It is essentially produced in the inner side of the plasma membrane when
the cell is in homeostasis; however, this asymmetry is lost during injury, malignancy, or
the apoptosis28,29. Under apoptotic conditions, cells reverse PS to the outer side of the
membrane. PS signalize to phagocytes that cell is under apoptosis30. The exact
processes, by which the cell externalizes these lipids, or how this process is initiated,
are not fully understood31. Cell cultures were analyzed 7 days after seeding, which
marks the beginning of the culture decay process. Hence, the two PS lipids elected as
markers for the control group, m/z 881 [PS(22:4(7Z,10Z,13Z,16Z)/21:0)] and m/z 903
[PS(22:0/22:0)] may be due to the apoptotic process that may have been initiated in the
cell culture, which lead to a higher dead cells ratio, as cell cultures are self-limiting in
growth. Additionally, since both cultures were analyzed at the same time point, the
ZIKV-infected group was likely in the same phase of the control one, which may explain
the lack of statistical significance in the quantitative analysis of markers between these
two groups. The level of all 6 PS characterized for the ZIKV-infected culture, m/z 516
32
[PS(18:4(6Z,9Z,12Z,15Z)/0:0)], m/z 518 [PS(18:3(9Z,12Z,15Z)/0:0)], m/z 520 [PS(18:2(9Z,12Z)/0:0)], m/z 540 [PS(20:6(2Z,5Z,8Z,11Z,14Z,17Z)/0:0)], m/z 542
[PS(20:5(5Z,8Z,11Z,14Z,17Z)/0:0)] and m/z 544 [PS(20:4(5Z,8Z,11Z,14Z)/0:0)], was
statistically significant in the semiquantitative analysis when compared to the control
uninfected culture, as shown in Figure 3.
PS seems to play a crucial role during virus infection8,11,29. The viral infection, in
turn, induces asymmetry in plasma membrane composition, similar to the
abovementioned apoptotic process, facilitating phagocyte recognition of infected cells32-
35. In addition, viral envelope phosphatidylserine are essential for viral replication,
mediating biding to target cells or phagocytosis of viral particles, such as demonstrated
for West Nile, Dengue and Ebola viruses8,11. Several recognition mechanisms of
apoptotic cells by phagocytes were described during the infection of several viruses,
such as those that recognize CD300a, TIM and TAM receptors, observed in DENV
infection8,9. In addition, the availability of PS in the outer side of circulating infected-
cells signals through TAM receptors to tighten cell junctions, modulating blood-brain
barrier integrity and preventing virus transit across brain microvascular endothelial cells
during viral infection36.
Phosphatidylethanolamines (PE)
PE, as well as PS, is an anionic lipid that is normally found in the inner side of
plasma membranes28,29, and are synthesized via the decarboxylation reaction of
PS37,38. It is the second most abundant lipid class in plasma membranes, after
phosphatidylcholines (PC)15. PE is externalized upon any cellular biochemical
imbalance28,29, probably by the same mechanism of PS, indicating that apoptosis is
underway39. As for PS, the three PE elected as markers for the control group (m/z 757
[PE(18:2(9Z,12Z)/19:0)], m/z 773 [PE(20:0/18:1(9Z))] and m/z 779 [PE(16:0/22:6(54Z,7Z,10Z,12E,16Z,19Z)(14OH))]) did not present significant
differences in content when compared to the ZIKV-infected group (data not shown).
Since PS and PE play the same role during apoptosis signaling39, the same premises
presented above may explain the lack of significance in this comparison.
33
Figure 3: Semiquantitative analysis of characteristic lipids showed that ZIKV-infected cells. The bars representing confidence interval of 95% (**** p<0.0001)
34
PE, as well as PS, is a substrate for TAM13 and CD300a8 receptors, involved in
viral internalization into the cell. The species elected as marker for the ZIKV-infected
group, m/z 632 [PE(12:0/16:1(9Z))], presented statistically significant differences in the
semiquantitative analysis (Figure 3), probably due to a cellular response mechanism
that uses this particular PE as an alert signal for phagocytes upon viral infection39.
Another potential explanation is that this PE is a component of the viral envelope during its replication (Figure 4).
Phosphatidylcholines (PC)
PC is the most abundant plasma membrane phospholipid, and its distribution,
as opposed to PE and PS, is on the outer side of the membrane. PC was only elected
as marker for the ZIKV-infected group, which presented greater amount of this
compound when compared to the -uninfected one (Table 1). This is in agreement with
similar findings reported for DENV-infected cell cultures14,15. The 4 PC elected as
markers for ZIKV infection (m/z 530 [PC(19:3(10Z,13Z,16Z)/0:0)], m/z 536
[PC(19:0/0:0)], m/z 556 [PC(6:2(3E,5E)/14:2(11E,13E))] and m/z 558
[PC(6:2(3E,5E)/14:1(13E))]) also presented statistically significant quantitative
differences (Figure 3), evidencing that there is a greater amount of these lipids in the
ZIKV-infected group, compared to the control one. Two out of the PC elected as
markers of ZIKV have already been previously associated to cell response against
infectious agents. The ion at m/z 530, which corresponds to
PC(19:3(10Z,13Z,16Z)/0:0) has already been found on the metabolome of bile acids in
patients with altered microbiota and pyloric sphincter40. Ion m/z 536, corresponding to
PC(19:0/0:0) was reported in a lipidomics study that analyzed inflammatory mediators
as potential biomarkers for bacteremia41; however, in this study made with blood
plasma, this species was implicated as a marker of uninfected, bacteremia-free
patients, as opposed to what was found in our in vitro study. Such difference may be
due to either the pathogen used in the study or the study type (in vivo vs. in vitro); in
35
Figure 4: Chemical images from MALDI-MSI showing the comparison between
infected and uninfected cells. It is visually possible to assess the difference in lipid composition of ZIKV-specific characterized biomarkers.
Figura 6: Chemical images from MALDI-MSI showing the comparison between infected
and uninfected cells. It is visually possible to assess the difference in lipid composition
of ZIKV-specific characterized biomarkers.
36
either case, both lipids are associated with a cell response to an infectious agent,
whose mechanism is yet to be elucidated40,41.
Furthermore, another study has demonstrated that infections caused by positive
RNA viruses, such as ZIKV, promote an increase or accumulation of PC – which is
utilized in the formation of viral replication complex (VRC), and also for the replication
of the virus in the VRC14 – a potential explanation for why those are the markers
displaying the greatest amounts in ZIKV-infected cells when compared to the -
uninfected ones (1.74-fold for ion 530 m/z, 1.96-fold for ion 536 m/z, 2.15-fold for ion
556 m/z and 1.94-fold for ion 558 m/z).
Other lipid classes
Three other lipids were identified as markers: two for the control group, a
phosphatidic acid at m/z 409, PA(16:0/0:0), and a triacylglycerol at m/z 925,
TG(18:2(9Z,12Z)/20:4(5Z,8Z,11Z,14Z)/20:4(5Z,8Z,11Z,14Z)); and one for the ZIKV
group, a diacylglycerol at m/z 925, DG(16:1(9Z)/16:1(9Z)/0:0). The latter may be
explained due to the increased metabolic activity of ZIKV-infected cells, since DG is
part of PE and PC synthesis, as well as Kennedy Pathways23,42. Once again, the other
two elected markers for the control group did not present significant differences in the
semiquantification when compared to the ZIKV group, indicating that these species
may be common in both cell cultures.
Our findings suggest that PS, PE, SL and PC specific-lipids are putative
biomarkers of ZIKV infection in C6/36 mosquito cells. These results are in line with
previous lipidomics studies of virus-infected cells. Previous contributions, especially
those that studied the same cell line (C36/6 mosquito cells) infected with DENV, have
observed increased profiles of lipids such as phosphaditylcholines (PC),
phosphatidylethanolamines (PE) and phosphatidylserines (PS) compared to the control
cells15, which are exactly the same view in our study. Furthermore, other recent study
also demonstrated higher level of lipid classes of PC, PE, PS and
37
phosphatidylglycerols (PG) during infection of brome mosaic virus (BMV) in YPH500
yeast14, indicating that these lipids are intimately involved with viral infection/replication
in different cell types and organisms. Hence, our results provide valuable information
on metabolites that may be used as therapeutic targets for further studies.
Acknowledgements
We are thankful to Professor Edson Durigon for kindly providing the ZIKV viral stocks
used in this work. We acknowledge funding from Fundação de Amparo à Pesquisa do
Estado de São Paulo (FAPESP – São Paulo Research Foundation), under the
following Grant numbers: 2011/50400-0 and 2015/06809-1 for RRC, 2014/00084-2 for
DNO, 2014/00302-0 for CZE, 2013/11343-6 for JASN) JANS is a FAPESP Young
Investigator. We also thank CAPES and CNPq for the fellowships for CFORM, EOL
and TMG.
Methods
Cell culture
The Aedes albopictus C6/36 cell line (ATCC® CRL-1660) was cultured in
special Leibovitz L-15 medium (Vitrocell®), with 1% of essential amino acids, pyruvate,
penicillin, streptomycin, and amphotericin (SigmalAldrich) and 10% of bovine fetal
serum – BFS (Vitrocell®). These cells were conditioned at 28ºC with 5% of CO2 at the
Animal Virology Laboratory of the University of Campinas.
Zika virus isolate
Brazilian ZIVK strain (BeH823339, GenBank KU729217) was kindly provided by
Professor Edison Durigon (Biomedical Sciences Institute, University of São Paulo).
This viral strain was originally isolated by a team of the Evandro Chagas Institute, Pará
38
State, Brazil from a Ceará’s State (Brazil) patient in 2015. The virus was stored at -
80ºC in the Animal Virology Laboratory of the University of Campinas until use. Before
procedure, the viral titer in this stock was determined by PFU assay in Vero cells.
Infection of A. albopictus C6/36 cells with zika virus
For ZIKV infection, 1x105 cells of C6/36 cell line was added to each well of a 24-
well plate, and incubated for 24 hours at 28oC with 5% of CO2. Viral Infection was
performed using a multiplicity of infection (MOI) of 10. The plate was then incubated
under 5% of CO2 for five days at room temperature. The same procedure was carried
out for the negative control samples, without ZIKV inoculation.
Viral detection by RT-qPCR
In order to confirm ZIKV infection, the viral stock and the supernatant of ZIKV-
infected C6/36 cells were assayed by real time RT-qPCR43. Briefly, the viral RNA was
isolated by a commercial kit following the manufacturer’s instruction (RNeasy Mini Kit,
Qiagen, Hilden, Germany). One step RT-PCR amplification of viral RNA (Taqman RNA
to-CT, Applied Biosystems) was performed with following primers and probes: ZIKV-F:
5’- CCGCTGCCCAACACAAG-3’; ZIKV-R: 5’- CCACTAACGTTCTTTTGCAGACAT -3’;
ZIKV-P: 5’-/FAM/AGCCTACCTTGACAAGCAGTCAGACACTCAA/-3’. All reactions
were assembled in a final volume of 12.5 μL with 300 ng of RNA, 1✕ PrimeTime mix
(Integrated DNA Technologies) containing both primers and probe, and 6.25 μL of
TaqMan master mix (Applied Biosystems) by using the following cycling algorithm:
48°C for 30 min, 95°C for 10 min, followed by 45 cycles of 95°C for 15 s and 60°C for 1
min.
MALDI-MSI analysis
Six days after infection, cells were placed on glass slides 24x60mm and
covered with MALDI matrix α-cyano-4-hydroxycinnamic acid (Sigma-Aldrich, St. Louis,
39
MO) solution at 10 mg/mL in 1:1 acetonitrile/methanol). Spectra were acquired using a
MALDI LTQ-XL (Thermo Scientific, San Jose, CA) at the mass range of 400 to 1200
m/z, in the negative ion mode. MS/MS data were acquired in the same instrument,
using Helium as the collision gas, with energies for collision-induced dissociation (CID)
ranging from 20-80 (arbitrary units). Spectra were analyzed using XCalibur software (v.
2.4, Thermo Scientific, San Jose, CA).
Structural elucidation
Lipids were identified based on the analysis of the MS/MS fragmentation profile
of the ions selected by statistical analyses. Structures were proposed using theoretical
calculations modeling for molecular fragmentation using Mass Frontier software (v. 6.0,
Thermo Scientific, San Jose, CA).
Semi quantification by MSI
Chemical images of the markers (Figure 4) were generated using the imaging
feature of MALDI and processed to grayscale using the ImageQuest software (Thermo
Scientific, San Jose, CA). All samples, control and ZIKV, and each respective replicate
(n = 15) had their chemical image standardized and analyzed using ImageJ software
(National Institutes of Health, USA – open source). A non-dimensional value was
assigned to each image based on pixel intensity, so that the intensity/quantity ratio is
established44.
Statistical analysis
Partial least squares discriminant analysis (PLS-DA) was used as the method of
choice to assess association between groups; this supervised method uses
multivariate regression techniques to extract, through linear combination of the original
variables, the characteristics that may evidence this association. Statistical significance
of the obtained model was assessed by using two permutation tests: precision preview
40
during modeling and separation distance; 2000 permutations were used in both tests.
The selection of lipids that were characteristic for each sample was carried out
considering the impact that each metabolite had in the analysis through VIP (Variable
Importance in Projection) scores, which consists of the weighted average of the
squares of the PLS loadings, and takes into account the amount of explained variance
on each dimension used in the model. As a cutoff threshold, only the chemical markers
with a VIP score greater than 1.5 were analyzed. The heat map of the VIPs was built
using the Pearson’s distance measurement and Ward’s clustering algorithm. All
analyses invoving PLS-DA and VIP scores were carried out using the online software
MetaboAnalyst 3.045.
For comparative purposes of semi-quantitative data, either Student’s t-test or
Mann-Whitney’s U-test was used after applying Kolmogorov-Smirnov normal
distribution test; a p-value was significant if it presented values higher than 0.05. All
those calculations (Figure 3) were carried out using the software GraphPad Prism
(v.3.0, GraphPad Software, San Diego, CA).
Competing financial interests
The authors declare no competing financial interests.
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