COLUMBUS, Ohio – In a new study of viral abundance over a short time frame in the Sargasso Sea, researchers found that almost all viruses with cyclical changes in abundance were most active at night – somewhat surprising when the team expected microbial behavior to pick up pace when light was available for photosynthesis.
It turns out the viruses most busy at night were not infecting bacteria that perform photosynthesis, which are among the types of bacteria known to be infected by viruses. Instead, these overnight viral hosts were microbes that focus on consumption of other organic matter because they can't produce their own food.
The findings reveal another level of complexity of viral interactions with marine bacteria, opening the door to new questions about how these dances in the dark influence ecological services provided by the world's oceans.
"We still don't know most of the genes that viruses have and what they do. So it's elucidating to know that these patterns exist for these viruses and their predicted hosts," said first study author Alfonso Carrillo , a PhD student in microbiology at The Ohio State University .
The rare look at microbial changes over a short time frame can also be used to inform future models designed to predict how the oceans will respond to warmer, more acidic water – the current conditions in the Sargasso Sea near Bermuda in the Atlantic Ocean.
"To understand how the ocean works as a whole, you can't exclude the viruses," Carrillo said. "It's important to understand how these viruses are behaving, how they're interacting with host bacteria, and how those interactions change over time. You can't really make models of how oceans will change unless you know all of these different frameworks."
The research was published recently in PLOS Biology .
Water samples for the study were taken as part of a long-term initiative called the Bermuda Atlantic Time Series .
The team sampled water from the surface and in an area called the deep chlorophyll maximum, or DCM, where a lot of microbes that perform photosynthesis are expected to be found. Over the course of 112 hours, they collected surface water every four hours and DCM water every 12 hours.
"We wanted to ask the question, do the viruses change between the depths and do we see any changes with regard to time? We expect it to change because the DCM has higher chlorophyll and there are differences in light, temperature and oxygen compared to surface levels," Carrillo said.
The composition of the viral communities present in each setting did differ, as expected, and the team then examined viruses that engaged in diel behavior – that is, cyclical changes in abundance within a 24-hour block of time.
Of the over 48,000 virus species collected, almost 3,100 showed diel behavior – and for about 90%, abundance peaked at night instead of during the day.
"This was unexpected because we thought the majority of the viruses that would have this kind of behavior may be performing photosynthesis or targeting bacteria that perform photosynthesis, but that wasn't the case," Carrillo said.
Instead, these viruses more active in the dark infected heterotrophic host microbes: those that eat other organisms because they can't produce their own food.
"That's interesting to us because it's something we hadn't seen before, and it's something that we can incorporate into future models about how viruses and their hosts might be behaving in the oceans," he said.
Carrillo works in the lab of Matthew Sullivan , professor of microbiology and civil, environmental and geodetic engineering and director of the Center of Microbiome Science at Ohio State, whose research program focuses on how viruses impact microbiomes in complex ocean, soil and human systems, including pioneering many experimental and bioinformatic approaches to "see" these impacts. Within that context, his lab is investigating how carbon cycling works in the oceans and the role viruses play.
Better, faster classification of viruses
Though the study of viruses and their functions in the sea, soil and our guts is advancing every day, the extent of what remains unknown about viruses far exceeds what scientists do know. A new analytical tool developed in Sullivan's lab is helping narrow that gap, using machine learning to establish a rapid classifier of virus samples.
"This tool allows researchers to organize the virosphere, which basically represents all the viruses that we know about," said first author Benjamin Bolduc , a computational scientist in microbiology. "And that's actually really important because if you don't know what viruses are related to other viruses, then it really impacts the kind of knowledge you can glean from whatever area of science that you're studying."
The paper was published recently in Nature Biotechnology .
Compared to its earlier versions, the updated tool, called vConTACT3 , expands the breadth and depth to which the organization of the virosphere extends in the biological classification of living organisms.
"For decades we've been looking at just the species, or just the genera, and that's important and relevant, but it doesn't give you any other information," Bolduc said. The new tool assists researchers in determining relationships at more general levels, such as family, order, class and phylum.
Previous versions of vConTACT also focused only on prokaryotes – archaea and bacteria that lack a nucleus – while vConTACT3 includes viruses that infect eukaryotes, organisms with a membrane-bound nucleus that include all animals, plants and fungi.
Because virus samples collected by researchers are often snippets of these organisms, their genomes are fragmented, and the lack of whole genomes has been a limiting factor in identifying viruses and, by extension, what they do in the environment.
Bolduc applied machine learning techniques at various stages of the development pipeline to identify patterns among genome fragments, which "helps overcome the fact you don't necessarily need the whole genome anymore in order to accurately classify a virus," he said.
The team assessed vConTACT3's performance against reference datasets and large databases of viral genome sequences.
"The tool is a big deal, increasing what virologists use to understand what new virus was discovered, and does so using knowledge-guided AI with some 60 million sensitivity analyses evaluated to fine tune it," Sullivan said. "It's also orders of magnitude faster than its predecessors at processing large datasets."
Both studies were supported by the U.S. National Science Foundation. Carrillo's work was also supported by the National Institutes of Health; Montgomery County, Maryland; and the University of Maryland. Bolduc's work was also supported by the German Research Foundation, the Alexander Humboldt Foundation and the Biotechnology and Biological Sciences Research Council.
Sullivan was the senior author of both studies. Co-authors of the PLOS Biology paper included Emily Hageman, Anna Mackey, Kimberley Ndlovu, Funing Tian, Dean Vik, Christine Sun and Richard Pavan of Ohio State; Lauren Chittick of Midwestern University; Naomi Gilbert of Lawrence Livermore National Laboratory; Daniel Muratore of Georgia Institute of Technology; Gary LeCleir and Steven Wilhelm of the University of Tennessee Knoxville; Ho Jang of Korea Virus Research Institute; and Joshua Weitz of the University of Maryland. Co-authors of the Nature Microbiology paper were Olivier Zablocki and Jiarong Guo of Ohio State; Dann Turner of University of the West of England; Ho Jang of Korea Virus Research Institute; Evelien Adriaenssens of the Quadrum Institute; and Bas Dutilh of Freidrich Schiller University.
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