Seasonal enhancement of the viral shunt catalyzes a subsurface oxygen maximum in the Sargasso Sea

Domain: physics
Published: 2025-12-06
Editorial outcome: minor_revision

Abstract
Subsurface oxygen maxima (SOMs) occur directly beneath the mixed layer of stratified water columns across oligotrophic open ocean basins and have been associated with physical transport processes and localized increases in phytoplankton net primary productivity (NPP). We explore the hypothesis that viral lysis (i.e., the ‘viral shunt’) increases nutrient recycling and enhances NPP, supporting SOM formation in stratified water columns, focusing on a recurring SOM at the Bermuda Atlantic Time-series (BATS) in the Sargasso Sea. Reanalysis of historical BATS data showed enhanced Prochlorococcus and virus-like particle abundances associated with SOMs. Instances of high rates of primary and secondary production observed with oxygen supersaturation further implicate a biological mechanism for SOM formation. Leveraging metatranscriptomes, metaviromes, and polony-based data collected during a Lagrangian cruise (October 2019), we link the viral shunt to SOMs, including evidence of elevated cyanophage abundance and infection of Prochlorococcus, and transcriptomic evidence of increased organic matter uptake (i.e., catabolic activity) by copiotrophic bacteria. Cruise data also showed Prochlorococcus nitrogen metabolism transcripts consistent with increased responsiveness to bacterial remineralization. These findings illustrate the biogeochemical impacts of enhanced viral lysis in marine systems, including the potential role of the viral shunt in facilitating SOM formation in the oligotrophic oceans.

Introduction
Marinemicrobialcommunitiesarenowfacingnovelphysicochemical environments and potential stresses as a result of changing climate feedback1.Inturn,shiftsinmicrobially-inducedecosystemfunctionmay influencebiogeochemicalcyclesofkeyelements,suchascarbonand oxygen.Quantitativepredictionsofthefeedbackbetweentheoceanand atmosphererequireincorporatinginformationonmicrobialprocesses andtheirresponsetophysicochemicalgradientsinthewatercolumn.In the oligotrophic open ocean, a significant fraction of atmospheric carbon dioxide is drawn down via oxygenic photosynthesis by phytoplankton2. Moreover,oligotrophic regions such as the Sargasso Seaconsistentlyexhibitsubsurfacezonesharboringdensephototrophic populations3,4, concurrent with high oxygen concentrations5,6. These regionsarereferredtoas“subsurfaceoxygenmaxima”(SOMs).

SOMs have been observed across oligotrophic open ocean regions that include the North Atlantic Subtropical Gyre5,6, the permanently stratified tropical and subtropical areas of the Atlantic Ocean7,theSouthPacificOcean8,theMediterraneanSea9,andsometimes even in large lakes10. SOMs can occur at 40–125m depth, depending ontheregionandseason11–13,andareformedbetweenthe uppermixedlayerandthedeepchlorophyllmaximum5,7.Theorigins of SOMsremain controversial. Whilesome combinationof physical and biological mechanisms are likely at work, literature analyzing subsurface oxygen dynamics in the gyres have posed hypotheses ranging from primarily physical (associated with isopycnal subduction)toprimarybiological(oftenascribedtophotophysiology).From aphysicalperspective,highlyoxygenatedwatersmaybesubducted and remain at high oxygen saturation because of their inability to ventilate6,9.Fromabiologicalperspective,enhancedprimaryproduction from microbial photosynthesis immediately below the mixed layer may generate elevated oxygen autochthonously8,9,12,13. At present, thereislimiteddirectexplorationofthemicrobialdynamicsthat occurattheSOM,despitethefactthatmicrobialactivityandinteractionsfundamentallyshapeoceanbiogeochemistry.Thus,although SOMsaresignificantandubiquitousacrossoligotrophicoceans,key biological mechanisms contributing to SOM formation and maintenanceafterseasonalstratificationremainelusive.

Toaccuratelyassessthecontributionofmicrobialinteractionsto primary production and the physical restructuring of water column depthstratarequireshigh-resolutionbiologicaldatainaphysicallywell- characterizedSOM.OnesuchcandidateoccursannuallyattheBermuda AtlanticTime-seriesStudy(BATS)long-termoceanographicmonitoring siteintheSargassoSea5.Long-termobservationsatdepthscommensuratewiththeBATS SOMrevealelevatedProchlorococcuscellabundances, heterotrophic bacterial densities, and particulate organic carbon3,5.Virus-likeparticleabundances(VLPs)havealsobeenreported toreachtheirmaximumlevelsbeneaththemixedlayeratBATSduring thestratifiedfall,coincidingwiththeemergenceoftheSOM3.Intheory, apeakinbiomassofthedominantmicrobialpopulationsattheSOM correlated to high VLPs would be consistent with the ‘viral shunt’ hypothesis,bywhichvirallysisenhances nutrientrecyclingandfuels primary production14–17. Moreover, historical reports of enhanced microbial and viral population abundances coinciding with the BATS SOMaswellasthepositiverelationshipsbetweenstratificationintensity, SOMformation,andprimary/secondaryproductionledustohypothesizethattheBATSSOMharborsamicrobialcommunityassociatedwith accelerated dissolved organic matter (DOM) recycling, coupled with enhancedvirallysis.AcceleratedDOMrecyclingandenhancednutrient retention mediated by viral infection could, in turn, result in oxygen accumulation in an isopycnal below the mixed layer, depending on balanceofprimaryrelativetosecondaryproductivity.

Here,wesetouttotestourhypothesisthatSOMsaremediatedby anenhancedviralshuntthroughmicrobialandbiogeochemicalcharacterizationofaBATS-proximalSOMsampledduringlatestratification.InOctober2019,overasix-dayLagrangiansamplingeffort,we collected day/night-resolving metatranscriptomes along with direct measurementsofpopulation-specificdensitiesofthedominanttaxa from depth profiles sampling above, at, and beneath the SOM. We quantifiedcyanophageabundancesandinfectionsintheSOMusing the polony and iPolony methods18,19 and community viromic assessment20, focusing on cyanophages capable of infecting Prochlorococcus.Ourresults,combininghigh-resolutiontemporalanalysis withhistoricaldatafromBATS,suggestthatenhancedvirallysisleads totightfeedbackbetweenphotoautotrophsandheterotrophsandthe repeated, seasonal emergence of SOMs in late fall associated with oceanstratificationinanarchetypaloligotrophicgyre.

Results
Seasonalstratificationisaccompaniedwithpersistentoxygen saturationandparticulatematterwithinthesub-mixedlayer

Depthprofileswerecollectedevery4haboardtheRVAtlanticExplorer onOctober12th,2019andendingonOctober17th,2019(Fig.1aandb). Densityprofilesderivedfromconductivity,temperature,density(CTD) measurementsindicatedahighlystratifiedupperwatercolumnwitha stablemixed-layerdeptharound50mforthedurationofthesampling period(Fig. 1c). A stable subsurface peak in oxygen saturation was apparent in the isopycnal about 5m beneath the mixed layer depth (Fig. 1d). This layer, which we refer to as the “SOM”, was situated approximately50mabovethedeepchlorophyllmaximum(DCM;Fig.1d ande,SupplementaryFig.1).TheSOMalsodisplayedthehighestbeam attenuationvalues,onaverage1.52-foldhigherthantheDCM(sd±0.14), and1.09-foldhigherthantheuppermixedlayer(sd±0.04),suggesting peak concentrations of particulate organic matter (POM) in the 0.5–20μmsizerange21,22(Fig.1fandSupplementaryFig.1).CTDprofiles measuredevery4hrevealadielcycleinbeamattenuationwithinthe SOM(RAINnonparametrictest,p<1e-10),suggestingtheseparticleshad growth/decaycyclesandwerenotsolelyallochthonousdetritus(Fig.1f). Theseobservationsareconsistentwithapreviousanalysisconductedat BATSwhichfoundenhancedcoloreddissolvedorganicmatter(cDOM) levelsassociatedwithelevatedbacterialabundanceandproductionin andaroundwhatweidentifyastheSOMlayer5.TheSOMduringour study had a mean increase of 22.14 (sd±4.20)μmol O/kg (11.57% increase)comparedtotheuppermixedlayer,andameanincreaseof 17.43 (sd±5.66)μmol O/kg (8.92% increase) compared to the DCM. Thesedifferencesresultinanaverageincreaseinoxygensaturationof 6.47% (sd±1.22%) in the SOM from the upper mixed layer, and an increaseinoxygensaturationof13.9%(sd±1.93%)intheSOMcompared totheDCM(Fig.1d).ThechlorophyllfluorescenceintheSOM,however, wasonly26.9%(sd±4.47%)thatoftheDCM(Fig.1e).

Wereanalyzedoceanographicclimatologicaldatacollectedfrom 1988to2019tocontextualizeourOctober2019cruisedatawithinthe physicalandbiogeochemicalcontextoftheBATSSOM.Priorworkon sub-mixed layer oxygendynamicsintheBATSregionusedprofiling floatdatatakenacrossfourseasonalcyclesfrom2010to2013andthe BATSchemicalmeasurementsoforganicmatter,oxygen,andnitrate toarguethatisopycnalsubductioncouldexplainoxygenaccumulationfrom50to100mduringthestratifiedseason,despitedrawdowns viaheterotrophicactivity6.Inouranalysis,wefocusonthe10mbelow themixedlayerdepthandexpandtherecordforanalysisbyusinga standardizedmethodofsensordataprocessingandthermodynamic conversions,calibratedagainstbottleoxygenmeasurementsusingthe Winklermethod(seeMethods)–resultingin5072CTDcastswithhigh- qualityoxygenprofilesspanning31years.Weusedtheseprofilesto characterize the change in mean oxygen saturation in the 10m beneath the mixed layer depth as a function of the time of year (Fig. 2b). Nonlinear least squares fitting of a sinusoidal regression identifiedanannualfluctuationinsub-mixedlayeroxygensaturation ofapproximately6.79%(6.71,6.88;95%CI,p<1e-10),fromabaseline of100.50%(100.42,100.59;95%CI,p<1e-10),withanannualminimum in mid-February (decimal year=0.123, 0.121,0.125; 95% CI, p<1e-10). Duetothesymmetryofthesinefunction,thissinusoidalregression indicatedamaximuminAugust(Fig.3).Theseresultssuggestthaton average, over the BATS climatology, the annual SOM’s intensity reaches its maximum in August. The maximum in sub-mixed layer oxygensaturationbuildsafterthedeepmixingperiodends(typically inMarch–April)toreachamaximuminAugust,untilitdissipatesatthe onsetofthenextdeepmixingeventinwinter(Fig.2a).Bydefiningthe SOM in reference to the mixed layer depth ascertained through a densitysurface-basedcriterion23,weadjustforyear-to-yearvariationin thedepthplacementofspecificisopycnals.Isopycnal-specificanalyses oftheisopycnalsurfacesthatliedirectlybeneaththemixedlayer(in the range of σθ= 24.4-24.6) show seasonal dynamics in oxygen saturationandtotalconcentrationwithtwopeaks–oneduringthe deep mixing in March (~95%), and another in August (~108%), suggestingoxygenaccumulationpost-stratificationinthenarrowbandof waterdirectlybeneaththemixedlayer(Fig.3).

Wealsoreanalyzedprimaryproductionandbacterialproduction experimentsconductedinsituoverthecourseoftheBATSclimatologywithafocusonthesubsetoftheseexperimentsthattakeplacein the SOM (approximately7 of112).We find that bacterial secondary production and carbon fixation positively correlated with oxygen saturationinproductionexperimentsconductedat40m-60m(SupplementaryFig.2).Furthermore,theexperimentsthathavethehighest oxygen saturation and most closely resemble a SOM also have the highestprimaryandsecondaryproduction ratesinthe BATSclimatology (Supplementary Fig. 2). Our findings of increased oxygen saturationinthenarrowdensitysurfacedirectlybeneaththemixed layerthroughoutthestratifiedperiod,aswellasobservationsofelevatedprimaryandsecondaryproductionratesmeasuredinthisnarrow feature, suggest that biological activity in the SOM – and not physical processes alone – drive oxygen accumulation. These processes are distinct from activity in the surface mixed layer and underlyingsubphoticwatersthroughoutthestratifiedperiod.

SOMmicrobialcommunityactivityismoresimilartothemixed layerthanthedeepchlorophyllmaximum

Wecollectedmetatranscriptomesfromdepthprofilesevery12h(day= 08:00, night = 20:00) during our Lagrangian sampling effort in October 2019 (Fig. 1b). These samples allowed us to compare the expressionof17,798,931genesacrosseukaryoticplankton,bacteria, andvirusesbetweentheuppermixedlayer,SOM,andtheDCM.We constructedaPCAordinationofmetatranscriptomegeneexpression profiles(SupplementaryFig.3).Theaxisexplainingmostofthevariation between metatranscriptomes (54.67%) separated the DCM samples from the other depths, meaning that SOM metatranscriptomesmorecloselyresemblesamplesfromthesurfaceandthe base of the mixed layer than the DCM (Supplementary Fig. 3). The second PCA axis, explaining 19.86% of total variance, established a gradientfromsurfacesamples(highestPC2values)tothebaseofthe mixedlayertoSOMsamples(lowestPC2values,SupplementaryFig.3). Metatranscriptomic profiles suggest the SOM microbial community transcription resembled the surface/base of the mixed layer more closelythanitdoestheDCM,withsomedivergenceincommunity- levelexpressionprofiles.

Next, we evaluated to what extent differences in community expressionwereduetodifferenceinmicrobialcommunitycomposition across these depth layers versus differences in the relative expression of different functional genes among shared taxa. We applied hierarchical clustering to taxon-specific expression of rpoB and RPB1,a pair ofcoreconserved housekeeping genes (RNApolymerase subunit B) spanning Archaea (rpoB), Bacteria (rpoB), and Eukaryota(RPB1)(Fig.4a).ThetaxonomicdistributionofrpoB/RPB1 transcriptsintheSOMmorecloselyresembledthatofthesurfaceand baseofthemixedlayerthantheDCM(Fig.4aandb).Thesurface/base of the mixed layer and SOM samples were characterized by high relative rpoB transcript abundances of the High-Light II Prochlorococcus ecotypes, and rpoB transcripts assigned to the orders FlavobacterialesandRhodospirillales(Fig.4a).TheSOMsampleshad elevated relative rpoB transcript abundances for the Protobacteria ordersPseudomonadales,Oceanospirillales,andDesulfuromonadales, theBacteriodetesorderCytophagales,andProchlorococcusHigh-Light I ecotypes relative to the surface/base of the mixed layer samples (Fig. 4). A peak in Prochlorococcus High-Light I ecotypes has been observedinaSOMintheMediterraneanSea24,25.Statisticalassessment ofcontig-levelrpoBandRPB1abundancedifferenceswithdepthalso identifiedsignificantly(BH-adjustedp<0.1)elevatedtranscriptabundances inthe SOM of contigs with rpoBs assigned to knowncopiotrophic taxa (e.g., Rhodobacterales, Flavobacteriales, Oceanospirillales, Cytophagales; Supplementary Fig. 4). These taxa were associated with environments analogous to phytoplankton blooms, for example, where algal-derived organic matter primarily supplies these rapid DOM recyclers26–29. A seasonal sub-mixed-layer Rhodobacteraceae maximum has also been previously observed at BATS3. Conversely, we observe genome “streamlined” heterotrophs suchasSAR116,SAR86,andSAR9230,thatareprimarilyactiveinthe surface/baseofthemixedlayerrelativetotheSOM(Fig.4a).

Wethencomparedthechangesinpopulationstructureasinferred throughthehousekeepinggeneanalysistodepthprofilesofcellcounts asdeterminedbyflowcytometry.Prochlorococcus,whichhadincreased transcriptional abundance in the SOM, also had increased cell abundancescomparedtothesurface(BH-adjustedp<0.0001),baseofthe mixedlayer(BH-adjustedp=0.0012)andDCM(BH-adjustedp=0.0229; Fig.5).PeaksinProchlorococcushigh-lightecotypeabundanceshavebeen observed below the mixed layer at BATS and the North Pacific SubtropicalGyre3,4.HeterotrophicbacterialcellabundanceswerealsoelevatedattheSOMcomparedtothesurface(BH-adjustedp=0.0351),base of the mixed layer (BH-adjusted p=0.0165), and DCM (BH-adjusted p<0.0001;Fig.5).Oxygensaturationabove100%inthisisopycnalcan result from greater primary production (O supply) compared to 2 respiration (O demand). While both primary producers and hetero- 2 trophshadoverallincreasedabundancesintheSOM,therelativeincrease ofProchlorococcuswashigher,withameanheterotrophicbacterium-to- Prochlorococcusratioof4.4asopposedto8.2inthemixedlayer(Supplementary Data 1). This suggests that oxygen supersaturation in the SOM could arise from disproportionate increases in Prochlorococcus (drivingincreasedprimaryproduction)relativetoheterotrophicbacteria.

TaxasharedbetweenthemixedlayerandSOMareenrichedin transportertranscriptsrelatedtonitrogenrecycling

Thejointanalysisofexpressionandcompositionisconsistentwiththe hypothesisthattheSOMsupportsamicrobialcommunitycontaining similar taxa to the surface and base of the mixed layer, but in an alternative functional state maintaining higher population densities and/or activities of heterotrophic bacteria and Prochlorococcus. To furtherexplorethishypothesiswecomparedfunctionalgeneexpressionprofilesofthesurface,baseofthemixedlayer,SOM,andDCM withgeneenrichmentanalysesbasedonorder-level(forheterotrophic bacteria),class-level(Eukaryotes),orgenus-level(forCyanobacteria, combining all Prochlorococcus ecotypes) aggregates of functional genesannotatedviaKEGGorthology[KO31].UsingratiosofKOtranscriptabundancestothecorrespondingrpoB/RPB1(“rpoBratio”;see Methods),weidentified604KO-annotatedgenesthathadeithersignificantly(BH-adjustedp<0.1)higher(193)orlower(411)transcripts relativetothattaxon’srpoB/RPB1expressionattheSOMcomparedto allothermeasureddepths,spanningeukaryoticandprokaryotictaxa (SupplementaryFig.5andSupplementaryData2).

Out of the 604 KO-annotated genes, 25 were assigned to Prochlorococcus (Supplementary Fig. 6a and Supplementary Data 2). Threeofthesehadsignificantlyhighertranscriptabundancesatthe SOMrelativetoallotherdepths(SupplementaryFig.6aandSupplementary Data 2). These are mrp (ATP-binding protein involved in chromosome partitioning; K03593), rpmG (large subunit ribosomal protein L33; K02913), and amt (ammonium transporter, K03320; Supplementary Fig. 6a and Supplementary Data 2). The Prochlorococcusammoniumtransporter,amt,hadthehighestrpoBratio attheSOM(~2.5amt:rpoB)comparedtoallotherProchlorococcusKOs. Prochlorococcusamtexpressionalsoincreasedatduskinthemixed layer,butnotattheDCM(SupplementaryFig.6b).

Seventy-fourKO-annotatedgenesbelongingtotheKEGG“transport” category assigned to eukaryotes, heterotrophic bacteria, and cyanobacteria were identified that were significantly (BH-adjusted p<0.1)higherorlowertranscriptvaluesattheSOMcomparedtoall other depths measured (Supplementary Data 2 and Supplementary Data3).Transportertranscriptsforinorganicnutrientssuchasiron/ other metals, phosphate, and nitrate were lowest at the SOM (Supplementary Data 3). Heterotrophic bacterial transcripts were significantly highest at the SOM included transporters for (nitrogen- containing)organicsubstrates,includingpolar/branched-chainamino acids,oligopeptides,andpolyamines(SupplementaryData3).While expressioncannotdirectlybesubstitutedforbiochemicalactivity32,we identifiedhighertranscriptionrelatedtouptakeoforganicnitrogen- containingmoleculesamongheterotrophsandenhancedammonium uptakebyProchlorococcus(thelatterofwhichismentionedabove), alongsidedecreasedexpressionoftransportersforothernutrientsby alltaxonomicgroups.Thisresultisconsistentwithincreaseduptakeof organic nitrogen-containing molecules among heterotrophs and ammoniumuptakeamongProchlorococcusattheSOM.

TheenhancedamtexpressionbyProchlorococcusattheSOMcould beduetodifferentphenomena.Increasedtranscriptlevelscouldbea responsetonitrogenstarvation33duetorapiddrawdownofnitrogen sources(includingammonium)bycompetingcells.Alternatively,this could be a response to enhanced ammonium availability. While amt transcriptionhasbeenshowntobeconstitutivelyhighforsomeProchlorococcusstrainsintheHLIandLLIVecotypes33–35,theadditionof ammoniumafterseverenitrogenstarvationresultedinanincreasein transcriptlevels34.Ammoniumisnotpartofthestandardsuiteofinorganicnutrientsmeasuredviamonthlycruise expeditionsatBATS,so historical observations of ammonium concentrations in the SOM are sparse5,36.Further,becausetherealizedconcentrationofnutrientsinsitu isinfluencedbyinput,production,drawdown,andabiotictransformation,extrapolatingrealizednutrientavailabilityfrommeasurednutrient concentrationsremainschallenging.SincentcAtranscriptionislowin thepresenceofsufficientammonium33,34,thecombinedfindingofsignificantlylowerntcAtranscriptlevels(SupplementaryFig.6a)andsignificantlyhigher amttranscriptlevelsnormalizedto rpoBtranscripts, suggestsahigherfluxofammoniumandaroleforthisnitrogenacquisitionpathwayforProchlorococcusattheSOM.

WeproposethattheenhancedamtexpressionattheSOMislikely duetoacombinationofphysicochemicalandbiologicalfactors,where Prochlorococcussatisfiesitsnitrogendemandundercompetitionvia rapid ammonium assimilation, as suggested in previous studies34,37. VerticalinjectionofammoniumtowardstheSOMfromdepthispossible,howeverenrichmentinamttranscripts is concentrated atthe SOMandnotattheDCM,suggestingadifferentsupplymechanism. Prochlorococcusamttranscriptlevelswerehigheratduskforboththe SOM and surface/base of the mixed layer (Supplementary Fig. 6b). Phototrophicamtexpressionhasbeenshowntooccurmainlyatdusk, andwaslinkedtoenhancedribosomeandproteinsynthesisexpressionatnight38.Thesepatternsarealsoconsistentwithdielexpression ofProchlorococcusamtinlaboratoryexperiments35.Thetransportof organic compounds by heterotrophic bacteria at the SOM likely also satisfies their carbon and nitrogen demand under competition, as copiotrophicbacteriaaresuitedtousediverseinorganicandorganic resourcesforgrowth29.Collectively,theseobservationsrelatetoeach other inthe context of the microbialloop – heterotrophic bacteria catabolizeDOM,excretingammoniumasabyproduct,fuelingcarbon fixation by primary producers,whowould then release DOM39,40.In thiscase,wehypothesizethatheterotrophicdegradationoforganic matter provided additional ammonium that supported Prochlorococcus growth. Our hypothesis led us to ask - what was the sourceofDOMforheterotrophs?

ElevatedsignaturesofviralinfectionofprokaryotesintheSOM

Virus-mediatedmortalityofProchlorococcusishypothesizedtobea significant contributor to the release of DOM into the viacellular environment14,15,41.Virus-inducedlysisandreleaseofDOMischallengingtoestimatedirectly19,henceproxiesforthestrengthofpotential virallysisareoftenused,includingviralabundance,thepercentageof infected cells when possible, and intracellular viral transcriptional activity.Here,wequantifiedcyanophageabundanceinthewatercolumnusingthepolonymethod18andfoundthat,on-average,T4-like cyanophagesweremoreabundantintheSOMthaninthemixedlayer by 3.12-fold (BH-adjusted p=0.0163) and 5.54-fold (BH-adjusted p=0.0007) relative to the surface and the base of the mixed layer respectively(Fig.6a,SupplementaryData1).Likewise,viatheiPolonymethod19,wefoundthatthetotalnumberofinfectedcellswashigher intheSOMby11.70-fold(BH-adjustedp<0.0001)and3.44-fold(BH- adjusted p=0.014) than inthe surface and baseof the mixed layer respectively(Fig.6b,SupplementaryData1).Thisequatestoroughly 2.8%ofProchlorococcuscellsinfectedbyT4-likecyanophagesatthe SOM(SupplementaryFig.7).

Additionally,wedetectedhigherfreeT7-likecyanophagesinthe SOMby19.62-fold(BH-adjustedp<0.0001),15.42-fold(BH-adjusted p=0.0002), and 2.79-fold (BH-adjusted p=0.1524) relative to the surface,baseofthemixedlayer,andDCMrespectively(Fig.6c,SupplementaryData1).ThetotalnumberofT7-likecyanophage-infected Prochlorococcus cells wasalsohigher in the SOM by 11.26-fold (BH- adjustedp<0.0001)and5.42-fold(BH-adjustedp=0.0057)relativeto thesurfaceandbaseofthemixedlayerrespectively(Fig.6d,Supplementary Data 1). This equates to ~4.1% of the population of Prochlorococcus being infected by T7-like cyanophages at the SOM (SupplementaryFig.7).Together,~7%ofProchlorococcuswasinfected bycyanophagesintheSOM.

Wealsoassessedtheintracellularexpressionofassembledvirus OperationalTaxonomicUnits(vOTUs)fromcollectedviromes,comparingtheirexpressionvaluesacrossdepth.First,weassignedvOTUs toT4-andT7-likephagegroupsbroadlyinfectingprokaryotesbased onthepresenceofhallmarkgenesandfoundthatawiderangeofT4- and T7-like vOTUs had the highest expression values at the SOM comparedtothemixedlayer(SupplementaryFig.8,seeMethodsfor hallmarkgenedetails).OnlyasmallersubsetofmostlyT7-likevOTUs hadexpressionvalueslocalizedtotheDCM(SupplementaryFig.8).

Next, using phylogenies of translated hallmark genes for T4-like (Gp23)andT7-like(DNAPolA)phages,weassessedputativevOTUs related toisolatedcyanophagesinfectingProchlorococcusandSynechocouchosts(SupplementaryFigs.9and10).PutativephagescaffoldsrelatedtoT4-likecyanophageisolates(SupplementaryFig.9)had 0.7–3.76and0.96–11.02log fold-changemoretranscriptsattheSOM comparedtothesurfaceandtheDCM,respectively(Supplementary Data4).PutativephagescaffoldsrelatedtoT7-likecyanophageisolates (SupplementaryFig.10)had2.06–6.23and1.43–6.23log fold-change moretranscriptsattheSOMcomparedtothesurfaceandtheDCM comparedtothesurfaceandtheDCM(SupplementaryData4).AlthoughT7-likecyanophageabundancewas highestattheSOM,thetotalnumberofT7-cyanophageinfectedcells attheSOMwassimilartotheDCM(Fig.6d,SupplementaryData1).We alsofoundtranscriptsforotherphagesrelatedtoviralisolatesknown toinfectheterotrophicbacteriathatweresignificantlyelevatedatthe SOM(SupplementaryFigs.9and10),suggestingthatenhancedviral replicationmaybeexpandedtobacterialtaxabeyondcyanobacteriaat theSOM.

The combined resultsindicate elevated viralinfection and productionofProchlorococcuscyanophagesaswellaselevatedtranscript abundances of heterotrophic phage in the SOM. Previous analysis found increases in virus-like particles (VLPs), representing the total dsDNAvirioplanktonparticleconcentration,intheSOMoveraperiod of10yearsatBATSconcomitantwithincreasesinProchlorococcusand bulk-Rhodobacteraceae cell abundances3 (see Supplementary Fig. 11 for reanalysis ofthese data with BATS oxygen profile data incorporated).Further,peakT4andT7-likecyanophageabundances(inferred intheviriacellularmetagenomes)havebeendocumentedbelowthemixed layeracrossoceanbasins42.Theelevatedstandingstockofviralparticlesandevidenceofheightenedlevelsofviralinfectionduringour LagrangiancruisesuggestthatalargepopulationofextracellularvirionsaremaintainedbyinfectionandreplicationattheSOM.Todate, all known Prochlorococcus phages are obligately lytic43,44, and lytic cyanophagehavebeenwelldocumentedatBATS45.Indeed,thepositionoftheSOMinthewatercolumnmayfavorlyticreproductionof viruses,aslightlevelsareattenuatedatthisdepth,reducingthelikelihood of viral particle inactivation via UV-induced damage46. Additionally,enhancednutrientavailabilitysuppliedtothehostcould playaroleinpromotinglyticinfectionattheSOM(reviewedinref.47). Altogether, these results suggest the SOM harbors increased viral infectionacrossmultiplebacterialtaxa,rangingfromcyanobacterialto heterotrophicbacterialhosts.

TowardatheoryofanenhancedviralshuntintheSOM

Inthispaper,weexploredpotentialecologicalmechanismsunderlying the recurrent feature of a SOM in the Sargasso Sea. We did so by assessingbothcellularandviralactivityproxiesofthecurrentBATS Lagrangian dataset along with detailed historical abundance data. ThroughouranalysisofhistoricalBATSdatatotracetheemergenceof theSOMoverthepast30years,wefoundcorroboratingevidencefora relationshipbetweentheSOM,primaryproduction,Prochlorococcus populations, and virioplankton abundances. By contextualizing our Lagrangiancruisestudywithlong-termdynamics,weproposethatthe SOM contains a microbial community with enhanced net primary production,acceleratedbyaseasonalviralshunt,whereinenhanced viralinfectionofprimaryproducersstimulatesheterotrophicorganic matterremineralization,providinginorganicnutrientstofuelprimary productionandoxygenaccumulation.

Previous studies have provided evidence that SOMs are associatedwithenhancedDOMlevelsintheformofcDOM,whichhasbeen shown to stimulate the growth of heterotrophic bacteria48. Other studies have shown bioavailable cDOM is enriched in the lysate of Prochlorococcusafterinfectionbycyanophage49.Metabolomicanalysis of marine bacterial lysates has also been shown to be enriched in aminoacidsandotherorganicnitrogensubstratesuponinfectionby Synechococcus phage50 and heterotrophic bacteriophages51–56. Catabolism of organic matter by heterotrophic bacteria produces abundant inorganic nitrogen in the form of ammonium, which Prochlorococcus competitively sequesters to satisfy its nitrogen demand37. Indeed, laboratory studies have demonstrated that DOM enrichment,drivenbyvirallysis,supportedphytoplanktongrowthby supplying excess ammonium17,57. Additionally, the increased dusk Prochlorococcus amt expression coinciding with enhanced beam attenuationatdusksuggestapotentialcouplingoftheseprocessesat the SOM. Indeed, the SOM in the stratified season likely supports optimallyticviralreplication,wherelightissufficienttoallowphototrophicmetabolism,yetattenuatedtopreventviralparticledegradation.Additionally,ourtranscriptomicsdatasuggestalleviatednutrient limitationbelowthemixedlayer,whichlikelycontributestoenhanced microbialabundancesandviralreproduction.

Overall,ourcombinedresultssuggestthattheSOMintheSargasso Sea arises as a recurrent biogeochemical feature from the combinationofseasonalshiftsinphysicalwatercolumnstructureand enhancedmicrobialactivity,atleastpartlymediatedbyviralinfection. Critically,ouranalysisof-omics,polony/iPolony,andhistoricaldata demonstratehowtheviralshuntmayplayacentralroleindrivingSOM biogeochemicaldynamics.Asstratificationisexpectedtointensifyand deepmixinganticipatedtoweakenduetoincreasedannualseasurface temperatures58,59,we expectemergenteffectsontheformation relativeimportanceoftheSOM,andconsequentlytheviralshunt,to biogeochemicalfluxesofcarbonandoxygen60.Ourresultsemphasize theneedtoincorporateviralinfectionintochangingoceanmodeling and prediction as a critical mechanism for understanding carbon remineralizationdynamicsinthesubsurfaceofoligotrophicoceans. Werecognizethatourinferencefocusesonaparticularstudysitein the oligotrophic Sargasso Sea and that insights derived from high- resolutiontemporalsamplinginarchetypaloceanbasinsremainlimited. Precisely so, we suggest thatfutureefforts should include targeted quantification of bulk- and single-cell viral infection, using a combinationofhigh-throughput(e.g.,single-celltranscriptomics)and host-resolved laboratory infection assays (e.g., iPolony) to more accuratelyquantifyviralcontributionstoSOMbiogeochemistry.Such effortswillenablebettermodelingandpredictionofmutualfeedbacks between climate variability, SOM formation, and the macroscale functionofSOMs.

Methods
SamplingdesignandAE1926CTDdataprocessing

Attheonsetofthestudy,asurfacebuoywithanunderwaterdrogue(at ~30mdepth)wasdeployedtoallowustofollowthesame“patch”of water for the duration of the study. Water samples were collected usingaCTD-rosetteequippedwith24×12-LNiskinbottles.Depthsfor eachcastwerechosenbasedoninsituCTDoceanographicparameters to allow for focus on water column features: this included the top (surface,surface)andbottom(baseofthemixedlayer)oftheupper mixedlayer,onedepthwithinthehighlyoxygenatedzonebelowthe mixedlayer(subsurfaceoxygenmaxima,SOM),andonedepthwithin thezonewiththehighestchlorophyllfluorescencevalues(thedeep chlorophyllmaxima,DCM).ForeachcasttheCTDwasdeployedtoat least500mtocollectdataonphysicalwatercolumnstructure.CTD profilesusedinFig.1arebasedonthewatercolumnprofilescollected every4hduringthesamplingcampaign.Watersampleswerecollected fromfourmaindepthsevery12hstartingat8:00ADT(GMT-3):~5m depth(surface),~40–50mdepth(baseofthemixedlayer),~42–60m depth(SOM)and105–120mdepth(DCM).

CTDdata were retrieved as deposited inBCO-DMO61. Measurementswerebinnedtothenearest0.5mofdepthtostandardizeacross casts,thenaNadaray-Watsonkernelsmoothingfilterwithbandwidth of5dbwasappliedtoeachvariabletoremovenoiseandspikiness. Mixedlayerdepthforeachcastwascalculatedusingthecriterionofan increaseinpotentialdensityof0.125fromareferencepressureof10db to account for instrumental noise in the surface62–65. Notably, this mixed layer depth criterion tends to identify the potential density surface directly below which oxygen saturation% increases to over 100%, operationally capturing the SOM depth as the first isopycnal (within 0.1kg/m3) below the MLD as defined using the 0.125kg/m3 change from surface criterion. This mixed layer depth criterion is presented as a preset commonly used in oceanographic timeseries dataarchives23.Forstatisticalcomparisonofdepthlayersanddepth layer-integrated time series analysis, smoothed data were averaged intodepthbinsrepresentativeofthoselayers–themixedlayerwas binnedfrom5to40m,theSOMfrom60to50m,andtheDCMfrom 120 to 100m. Beam attenuation, chlorophyll fluorescence, oxygen concentration,andoxygensaturationwereallaveraged(mean)across these layers. The beam attenuation measures particles within the 0.5–20μmsizerange21,22.Fordielperiodicityanalysis,datawereinitially detrended using a linear model, and then the nonparametric rhythmicitydetectionmethod‘rain’v.1.30.066wasrunin‘independent’ modewithatestperiodof24h.

BATSCTDdataprocessing

CTD cast data from October 1988 through December 2019 were downloadedfromtheAPIavailableathttp://bats.bios.edu/bats-data/ and in ASCII format. Bottle data were also downloaded from the API availableatbatsftp.bios.edu/BATS/bottle/bats_bottle.txtinASCIIformat. Data on experimental rate measurements from BATS isotope incorporationexperimentswerealsodownloadedfromtheBATSAPI (currentlyavailableviathedropboxlink:https://www.dropbox.com/ scl/fo/x7xvlmyzqh9t9tfpe8ffg/AEBrkFFxVFvlO31MJmd9pcY?rlkey= 7v73mfwhd78fdtxvfhk4v4kca&e=1&dl=0). Rate data were matched withthecorrespondingCTDcastintheBATSCTDdatarecordand experiments taken between May and October (the months where stratificationtypicallyoccurs)conductedabove200mwereusedfor further analysis. After initial reformatting to account for inconsistenciesinfileformatsbetweencasts,anycastwithfaultyormissing dataforconductivity,temperature,orpressure,aswellascastsmissingdatafromthetop10dbofpressurewereremovedsothatallcasts could have the same thermodynamic calculation processing. The remaining5270CTDprofileswerethenprocessedusingmethodsfrom theGibbsSeawaterToolbox(https://www.teos-10.org/pubs/gsw/html/ gsw_front_page.html)usingthepython3.4.0distributionthroughRvia the reticulate package v1.24 (https://github.com/rstudio/reticulate). Briefly,heightfromsurfaceofgeoid,potentialsalinity,absolutesalinity,conservative temperature,potentialdensity(sigma-theta),oxygensolubility,andoxygensaturationwerecalculatedusingpressure, longitude,latitude,temperature,conductivity,andoxygenCTDdata. Mixed layer depth was calculated as described above. Bottle data, includingflowcytometrydata,werealsodownloadedfromtheBATS APIandmatchedtocorrespondingcastsanddepths.Thequalityof CTDoptodedatawasassessedthroughasystematiccomparisonof CTD oxygen values to bottle measurements using the Winkler method67.Alinearregressionwasusedtoassessthecorrespondence between methods. The fit was [O µM via CTD 2 optode]=7.85+0.964*[O µMviaWinklermethod]withanadjusted 2 R2=0.959. Any cast with a measurement containing a standardized residualof3orgreater,indicatingalargediscrepancybetweenCTD optodeandbottleoxygenmeasurements,wasdiscardedforfurther analysis(totalof26/5270casts).

Prochlorococcus-virusseasonalrelationshipmodeling

VLP counts associated with BATS monthly time series cruises from Parsons et al., were retrieved from supplementary information and matched to corresponding BATS time series cruise bottle and CTD data, processed as described in the above section. Altogether, 104 observationswerepairedresultinginProchlorococcusflowcytometric counts from BATS publiclyavailable bottle data, oxygen concentrationsfromBATSCTDdata,andVLPcounts.Datawereseparatedby month to estimate monthly varying effects on the relationship betweenProchlorococcusandVLPs.Foreachmonth,atype-IIregressionmodel(majoraxisestimationprocedure)wasfitusingtheRv4.2.1 packagelmodel2v.1.7-368forlog Prochlorococcuscountsandlog 10 10 VLPs.Theslopeofthislinearmodelonlog-logdataisequivalenttothe exponentofapower-lawrelationshipbetweenProchlorococcuscounts and VLP counts. Parameter estimate uncertainty and model significance were assessed using a permutation test with 10,000 permutationspermodel.

Metatranscriptomesampling,processing,andbioinformatic analysis

Seawaterwasfilteredthrougha0.2-µmpore-sizeSterivex™filtration unit.Residualwaterwasremovedbypushingairthroughthefilterwith a 60ml syringe, and the filter immediately transferred to a −80°C freezer within 1h of sample collection. RNA was extracted using a publiclyavailablephenol-chloroformbasedprotocol69withDNAcontamination removed using the Turbo DNA-free™ kit (Ambion®). Metatranscriptome libraries were prepared by reducing ribosomal RNAusingtheQIAGEN’sFastSelectkit(5S/16S/23SforbacterialrRNA depletion)andsequenced(2×151nt)usingthelow-inputprotocolfor totalRNAontheIlluminaNovaseqS4platformundertheDOEJoint GenomeInstitute(JGI)CommunitySequenceProposalID#505733.For sampleswith<10ngofRNAtotal,theultra-lowinputprotocolwas used(13PCRcyclesversus10cyclesforstandardlow-input).Specific librarypreparationmethodsusedforeachsamplecanbefoundonthe JGIGenomePortal(ProjectID505733).

RawreadfilteringandtrimmingweredoneusingBBDukv38.67 and BBMap v38.84 from the BBtools packages70. Trimmed filtered readswerecombinedacrosssamplesandassembledusingMEGAHIT v1.2.971. MetaGeneMark v3.38 was used to call open reading frames (ORFs)withakmersizeparameteras--k-list23,43,63,83,103,123.For thecellularcommunity,trimmedfilteredreadsweremappedtothe combined assembly using BBMap v38.8470 with defaultparameters, andtabulatedusingfeatureCountsfromtheSubreadpackagev.2.0.172. ORFproteinsequenceswereannotatedusingeggNOG-mapperv2.1.473 for functional annotation, and aligned to the PhyloDB database (https://github.com/allenlab/PhyloDB) using the software package EUKulele v.2.1.074 for taxonomicannotation of bacteria, eukaryotes, andarchaea.ORFswerefilteredwithaveragereadcounts≥10across the dataset. Variance stabilizing transformation (VST) using the DESeq2v.1.34.0R-packagewasusedforreadnormalization75.

We used theKyotoEncyclopediaofGenesand Genomes (KEGG) orthology annotations31 to explore actively transcribed metabolic pathways. Normalized read counts for each KEGG orthologue were summed for the genes assigned to each taxon within each sample, resultinginorder-levelsignalsforheterotrophicbacteria,genus-level forcyanobacteria,andclass-levelforeukaryotes.Toassessdifferences betweendepth/time,wecalculatedtheratioofeachKEGGKOVSTto the corresponding order-level summed VST of rpoB/RPB1’s (DNA- directed RNA polymerase subunit-beta/large subunit, K04043 and K03006) which assesses relative taxonomic contribution to each sample76, resulting in a “KO vst:rpoB ratio” to correct for positive correlationsbetweenincreasesingeneabundancewithtaxonabundance.Thisapproachhasbeenrecommendedforadjustingthegene transcript abundance to the taxon-level RNA estimate within each sample77whenpairedmetagenomicdataarenotavailable.

MetatranscriptomerecruitmenttoSingle-Celled-Amplified genome(SAGS)ofProchlorococcus

ToresolvespatialandtemporalpatternsinProchlorococcusecotypes, we competitively recruited metatranscriptome reads to publicly available SAGS from Berube et al.78. SAG genomic assemblies, gene annotations from the IMG Annotation Pipeline version 4 (accommodatingphylogeneticinformationpertainingtoecotypeandcladeof each SAG) and the cyanobacterial concatenated phylogenetic tree wereretrievedvia:
https://figshare.com/articles/dataset/File_12_Genome_sequences_ and_annotations/6007223?backTo=/collections/Single_cell_ genomes_of_i_Prochlorococcus_i_i_Synechococcus_i_and_sympatric_ microbes_from_diverse_marine_environments.

Trimmed, filtered reads were competitively mapped to a concatenated file containing all SAG genomic assemblies using BBMap v38.8470withdefaultparametersandtabulatedusingtheGFFfilegene coordinateswithfeatureCounts72.OnlySAGSthathad≥10%oftheir genes mapped to transcripts were considered ‘detected’ to avoid capturing spurious read recruitments79 and genes with <20 reads mapped across the entire timeseries were filtered out. Reads were normalizedusingtheVSTmethod75.

Statisticalanalysisofmetatranscriptomedata

Statistical analyses were performed using the R Statistical Software v4.1.380.Principalcomponentsanalysis(prcomp()inR)wasperformed onVSTnormalizedvaluesacrossallORFsdetectedinthemetatranscriptome assembly. The Kruskal-Wallis test (kruskal.test via stats v.4.3.1)followedbyDunn’smultiplecomparison(dunn.testv1.3.5)was used to determine significance of trends between depths (surface, baseofthemixedlayer,SOM,DCM)

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "In “Seasonal Enhancement of the Viral Shunt Catalyzes a Subsurface Oxygen Maximum in the Sargasso Sea,” Gilbert et al\nused transcripts, polonies for cyanophage abundance, and ipolonies for picocyanobacterial infection on a cruise in the\nSargasso Sea in October 2019. They combine this data with a re-analysis of BATS oxygen and viral-like particle timeseries\ndata. The purpose of the paper is to link Subsurface Oxygen Maxima (SOM) to Prochlorococcus productivity and viral lysis.\nThey found increased numbers of Prochlorococcus cells, cyanophage viruses, infected Prochlorococcus cells and\ncyanophage transcriptional activity at the SOM. In the literature, viral lysis is often linked to biogeochemistry in a vague\nhand-wavy way, so any paper that can link the two in a concrete fashion is very cool. I was happy with the bioinformatic\nanalyses and the polonies are always interesting and useful. This paper is very interesting, but it could be pushed a bit\nfarther to be a better paper. Particularly, the authors should incorporate existing primary productivity and bacterial\nproductivity measurements from BATS to see if that data upholds their hypothesis. Also, rather than simply dismissing the\nphysics aspects, it would be good if the physics was included in a small way (see below). And please make sure that the\nDOE/JGI sequencing is submitted to NCBI and acknowledged appropriately.\nOne thing that I found confusing about this paper was that it starts sounding like it is known that the Sargasso Sea and BATS\nhave SOMs, but then the first thing the authors do is prove that BATS has SOMs. Chen and McKinley (2019) analyzed 26\nyears of BATS data plus floats. It would good to know what this current paper did that was different. I think they just had to do\nthe work over again because the authors are non-overlapping.\nOn that same note, the authors have set up a physics versus biology argument in the Introduction, and they are clearly on the\nbiology side. However, the real ocean isn’t physics or biology, it is physics and biology. Chen and McKinley (2019) say that\n“After the spring bloom, surface waters that are enriched in oxygen and organic matter, but low in nitrate, are subducted and\ntransported along the seasonal isopycnals that progressively displace downward.” So physics is definitely happening. And\nthe authors have the timeseries data to see that the physics is happening. It would be great if this could be a physics AND\nbiology type of paper. How much more oxygen was there in August compared to when the water subducted in the spring?\nAlso, the question is really about primary production rates versus rates of heterotrophy. While it does not seem that these\nrates were measured on the cruise in question, primary production rates are measured at BATS. Are the rates higher or\nlower in the SOM below the mixed layer compared to mixed layer? Bacterial production is also measured at BATS, or at\nleast was in Steinberg et al 2001. Please incorporate these data into your arguments. Are rates of primary production greater\nthan bacterial production? This information is critical to understanding what is going on in the SOM.\nDetailed comments\nI received this paper to review from Nature Communications. My impression is that Nature Communications has a\nrequirement for separate Results and Discussion sections (though I defer to the editor on this). This paper needs Results\nand Discussion headings.\nLines 56-61: ipolonies, numbers of infected Prochlorococcus, were left out of this sentence. However, they are the\nsmoking gun!!! Please add in.\nline 87: the references are for the phototrophic populations and there are no citations for the oxygen concentrations. I guess\nChen and McKinley 2019 should be cited here.\nLine 100: Could this be elaborated on? What exactly is still elusive? The paragraph kind of makes it sound solved already.\nThere is some room here to elaborate.\nLine 102: use a comma instead of a dash\nLine 155: List the range of years that these CTD casts come from: (1988-2019). Readers get to the methods last in these\npapers and so need some help.\nLines 171-172: You could quantify this. How much more oxygen was there in August compared to when the water\nsubducted?\nLine 179: Order by depth: upper mixed layer, SOM, DCM\nLine 183: The abbreviations are getting excessive here. I think you can write out the word surface. Also, just write out base of\nthe mixed layer. Excessive abbreviation are a barrier to reader understanding.\nLine 197 etc: using metagenomic data, (Fuchsman and Hays, 2023; Fuchsman et al., 2023) clearly show the same\nProchlorococcus ecotypes in the mixed layer and right below the mixed, but different ecotypes dominating the DCM in the\nsubtropical North Atlantic. Also some good information about cyanophage dynamics.\nLine 210: were. Past tense\nLine 219: I am not sure what sub-surface mixed layer peaks means. I mean, I figured it out, but maybe explain more clearly.\nLine 228-230: Really you want primary production rates and bacterial production rates for these analyses. Not cell numbers.\nLine 254 and lines 268-274: There is usually an ammonium peak at the DCM or right below the peak of the DCM. So this is\neasily explained. You can see such an ammonium peak in (Widner et al., 2018) in the Pacific, but there must be similar data\nfrom the Atlantic. I believe it is a typical feature in the ocean.\nWoodward and Rees (2001) Deep Sea Research Part II shows the ammonium peak in the Atlantic. There is also Rees et al\nI think you can assume this feature is also present at BATS.\nLine 259: lower than the mixed layer? Or the DCM?\nLine 274: That is really too bad!\nLine 311: Also seen in (Fuchsman and Hays, 2023)\nLine 344: viral isolates\nLine 432: lol! I am sure you can find a paper than uses these criteria, which would be better than a webpage. Probably one\nof Dave Karl’s tomes. Anyway, fix this.\nKarl et al 2021 says “depths of upper mixed layer based on the density criterion of de Boyer Montegut et al. (2004),” so\nmaybe track down that one.\nLine 435: List the shallower depths first\nLine 454-455: You already said how you calculated the mixed layer above.\nLine 478-480: Do you have a time estimate of how long it took to get the RNA from the Niskin bottles to the freezer? This is\ncritical for determining quality.\nLine 644: This sequence data needs to be submitted to NCBI SRA. The people at JGI will do this for you. But it needs to be\ndone. And you need to add a supplemental table with all of the accession numbers and numbers of good quality reads.\nLine 644: The BATS bottle data should also be specifically listed out here.\nLine 658: I also have a DOE CSP grant and was told to also include the award doi in publication. I think you should also be\nacknowledging the staff that helped with sequencing and sequence analysis. Please look at the directions related to your\naward.\nPlease put the supplemental figures and their figure captions into one combined word document!!!!!!!!!!!!!!!!!!!\nSince this is now a Nature Communications Document, the authors could take a few of the many supplemental figures and\nmake them main document figures. I would recommend moving Figure S2 (SOM data from BATS) and Figure S4\nProchlorococcus ecotypes. It clearly shows that the SOM is more similar to the mixed layer than to the DCM.\nBibliography\nFuchsman, C.A., Garcia Prieto, D., Hays, M.D., and Cram, J.A. (2023) Associations between picocyanobacterial ecotypes\nand cyanophage host genes across ocean basins and depth. PeerJ 11: e14924.\nFuchsman, C.A. and Hays, M.D. (2023) Increased cyanophage infection at the bottom of the euphotic zone, especially in the\nfall. Environ Microbiol 25: 3349–3363.\nWidner, B., Mordy, C.W., and Mulholland, M.R. (2018) Cyanate distribution and uptake above and within the Eastern\nTropical South Pacific oxygen deficient zone. Limnol Oceanogr 63: S177–S192.", "reviewer_2": "Gilbert et al. is a study examining the role of viruses in the formation of SOMs in water at the BATS site. Using geochemistry,\ntranscriptional activity, and cell counts over timeseries they conclude that viral predation enhances oxygen production and\nNPP. The manuscript is well written, and the approaches are adequately support the conclusions. There are no major issues\nwith this study.\nSpecific issues:\nLn 85 - Suggested re-wording to remove the repetition of \"by\" in this sentence.\nLn 260 - Suggested change to: that were significantly\nLn 272 - Are the strains in the SOM part of this group with constitutively high amt transcription?\nLn 287 - Are there references that could be cited here to back up this assumption that transporters are induced in the\npresence of their substrates?\nLn 432 – missing citation\nLn 435 - This doesn't matter for understanding but this sentence may read more easily if all the layers are listed from either\nminimum to maximum (i.e. 5-40 m, 100-120 m, 50-60 m) or max-min.\nLn 551 - Which Illumina instrument was used?\nLn 558 - The recommendation for clustering on large-scales (>1,000s of sequences like you have here), according to the\nClusterGenomes github page, is to use anicalc and aniclust in the CheckV distribution instead of ClusterGenomes.\nI would recommendation to re-run anicalc and aniclust from CheckV and verify the ClusterGenomes clustering accurately\nclustered the large number of viral sequences from this study.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature\nCommunications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career\nResearchers who co-review manuscripts."}, "author_response": "We thank the reviewer for the comments and feedback. We have endeavored to\naddress all their critiques in the revision (and address them point by point below).\nOne thing that I found confusing about this paper was that it starts sounding like it is\nknown that the Sargasso Sea and BATS have SOMs, but then the first thing the authors\ndo is prove that BATS has SOMs. Chen and McKinley (2019) analyzed 26 years of\nBATS data plus floats. It would be good to know what this current paper did that was\ndifferent. I think they just had to do the work over again because the authors are non-\noverlapping.\nWe agree: the presence of an SOM in the Sargasso has been known for some time as\nthe author points out - both Steinberg et al (2001) and Parsons et al (2011) (both cited\nin the paper). Like Chen and McKinley (now cited in the revision), these authors display\nthe data across the calendar year, averaged by month. We reanalyzed oceanographic\nclimatological data collected from 1988 to 2019 to contextualize our October 2019\ncruise data within the physical and biogeochemical context of the BATS SOM. In the\npresent case we also provide the data by month in order to show the consistency of the\nresult (see Figure 2B). Notably, while Chen and McKinley use 26 years of BATS bottle\noxygen data. In our analysis, we focus on the 10m below the mixed layer depth and\nexpand the record for analysis by using a standardized method of sensor data\nprocessing and thermodynamic conversions, calibrated against bottle oxygen\nmeasurements using the Winkler method (see Methods) – resulting in 5,072 CTD casts\nwith high-quality oxygen profiles spanning 31 years. This gives our analysis higher\ndepth resolution over the full time series (see Figure 2B, Figure 3). We have now\nelaborated on these points, clarified the context, and provided more information on the\nmethodological difference that we then leverage to contextualize the October 2019\ncruise (Lines 157-184).\nOn that same note, the authors have set up a physics versus biology argument in the\nIntroduction, and they are clearly on the biology side. However, the real ocean isn’t\nphysics or biology, it is physics and biology. Chen and McKinley (2019) say that “After\nthe spring bloom, surface waters that are enriched in oxygen and organic matter, but\nlow in nitrate, are subducted and transported along the seasonal isopycnals that\nprogressively displace downward.” So physics is happening. And the authors have the\ntimeseries data to see that the physics is happening. It would be great if this could be a\nphysics AND biology type of paper. How much more oxygen was there in August\ncompared to when the water subducted in the spring?\nWe agree with the reviewer that the SOM has both physical and biological components.\nThe central goal of the present paper is to elucidate mechanisms underlying the\nbiological component of the biogeochemical change, which the reviewer supportively\nmentions we do ‘in a concrete fashion’. Our study reveals mechanistic evidence linking\nthe viral shunt mechanism to SOMs. This does not preclude an analysis of the physics\nin future work, but as we have argued, connecting an enhanced viral shunt to SOM\npersistence is both novel and ecologically relevant.\nThat said, from our reanalysis of an updated version of the Chen and McKinley review\nof the BATS history (now with an additional 5 years of data included in this paper), we\nfound two peaks in isopycnal oxygen content and oxygen saturation from isopycnals\nthat lie between the average mixed layer density in the stratified period (< about 1024.4\nkg/m^3 from our analysis) and those that subduct below the SOM depth (about 1024.6\nkg/m^3) - the first peak we associate with initial ventilation upon deep mixing (March\npeak) followed by a second peak post-subduction in July that is on average 2-5% higher\nO concentration immediately post-ventilation. We argued that this secondary\n2\naccumulation in oxygen total concentration and saturation likely has a biological\ncomponent, given that the increase occurs following the annual timing of restratification.\nChen and McKinley, who strictly invoke a physical mechanism of isopycnal subduction\nto explain seasonal dynamics in subphotic oxygen at BATS, indeed find evidence\nconsistent with our hypothesis that enhanced oxygen production occurs only in an\nextremely specific physical environment directly beneath the mixed layer depth, where\nsomething different is occurring than the net heterotrophy they propose for the\nsubducted isopycnals at slightly deeper depths. These data are presented in their main\ntext figure 3e, where it is clear that the along isopycnal change in O2anom, in the small\n(5-10m) window directly beneath the mixed layer depth during the stratified period (the\nred shaded area directly underneath the MLD marked with the black line), there is a\npositive change, unlike the negative change underneath it associated with the broader\n50-100m depth strata that they focus on for their broader analysis.\nWe have reworked the paragraphs in lines 157-197 to reflect our analysis that sustained\nO saturation and concentrations likely have something to do with a change to the\n2\necology and biogeochemistry brought about by the physical dynamics alluded to by\nChen and McKinley. Further, we have adapted Figure 2a in addition to moving our\nprevious supplementary figure on oxygen saturation dynamics to the main text (see\ncomments below). Now, Figure 2a shows oxygen saturation instead of oxygen\nconcentration, removing effects from changes in solubility due to temperature changes\nfrom seasonal mixing and isopycnal subduction. We also added grey contours of\nisopycnal surfaces at 0.1 kg/m^3 resolution in addition to the average mixed layer\ndepth. We hope this helps to illustrate along-isopycnal changes in oxygen saturation\nover the seasonal cycle. This figure now shows the increase in oxygen saturation after\ndeep mixing in the narrow band of isopycnals directly beneath the mixed layer, as\nopposed to increases in total oxygen concentration that occur across a broader range of\ndepths.\nAlso, the question is really about primary production rates versus rates of heterotrophy.\nWhile it does not seem that these rates were measured on the cruise in question, primary\nproduction rates are measured at BATS. Are the rates higher or lower in the SOM below\nthe mixed layer compared to mixed layer? Bacterial production is also measured at\nBATS, or at least was in Steinberg et al 2001. Please incorporate these data into your\narguments. Are rates of primary production greater than bacterial production? This\ninformation is critical to understanding what is going on in the SOM.\nWe agree with this suggestion and have examined the historical rates. However, the\nBATS record generally missed the SOM because of sampling at standardized depths\nthat do not focus on dynamic water column structure (this is common in many long term\ndata sets). What we can see, based on our analysis, is that during the stratified periods\nin the few times (~7/112 experiments we analyzed) where the sampling did overlap the\ninstances of primary production (PP) and bacterial production (BP) are positively\ncorrelated with high oxygen saturation (Figure S2). However, given the paucity of rate\ndata aligned to SOMs in the historical record, we cannot statistically conclude whether\nPP or BP rates were higher/lower. This analysis, combined with our flow cytometry data\nshowing a lowered ratio of heterotrophic bacteria to Pro at the SOM (Lines 245-250_,\ncould suggest higher primary productivity relative to secondary productivity. However,\nas stated later in the review, cell counts don’t necessarily equate to higher/lower rates of\nPP or BP. Yet, we will include the new rate data in supplemental and discuss our\nanalysis within the main text, but given that the survey does not directly sample the\nfeatures of interest for this study we do not include it as a main figure. We have included\nthe analysis of the existing BATS rate data as a supplemental figure (Figure S2), briefly\nreport the findings in the abstract (lines 61-62), results (lines 185-197), and added\nmethodology (line 473-480).\nDetailed comments\nI received this paper to review from Nature Communications. My impression is that\nNature Communications has a requirement for separate Results and Discussion\nsections (though I defer to the editor on this). This paper needs Results and Discussion\nheadings.\nWe have adjusted the manuscript structure to include a combined Results and\nDiscussion section header following the Introduction, and have kept the sub-sections\nthroughout the results and discussion with italicized subheadings. We made the ultimate\ndecision to keep the results and discussion combined based on the collective feedback\nthat there is too much discussion within each sub-section to just call it “results”.\nHowever, we also defer to the editor for the final decision on this point.\nLines 56-61: ipolonies, numbers of infected Prochlorococcus, were left out of this\nsentence. However, they are the smoking gun!!! Please add in.\nAddressed. We have know included the observation of elevated infection rates of Pro in\nthe abstract (line 65).\nline 87: the references are for the phototrophic populations and there are no citations for the\noxygen concentrations. I guess Chen and McKinley 2019 should be cited here.\nThe appropriate references have been added for the oxygen reference (Chen and McKinley\n2019, Steinburg et al. 2001). Line 82.\nLine 100: Could this be elaborated on? What exactly is still elusive? The paragraph kind\nof makes it sound solved already. There is some room here to elaborate.\nThe elusive part is the specificity of how microorganisms/the microbial foodweb\n(\"biology), potentially contribute to formation of SOMs. Specifically, dominant\nphototrophs such as Prochlorococcus playing a role as well as the often overlooked\nviruses that infect these populations (previous studies only counted particles). At\npresent, no analysis of data on microbial activity exists to specifically ask questions\nabout the potential role of microbes in SOMs. We included a few sentences highlighting\nthe lack of microbial ecology studies at the SOM which hopefully helps the reader\nunderstand what we feel is still elusive – Lines 96-100.\nLine 102: use a comma instead of a dash\nThe original sentence was reworded and no longer includes a dash (lines 102-103).\nLine 155: List the range of years that these CTD casts come from: (1988-2019).\nReaders get to the methods last in these papers and so need some help.\nThe range of years has been replaced “since 1988 to 2019”. Line 155.\nLines 171-172: You could quantify this. How much more oxygen was there in August\ncompared to when the water subducted?\nWe have included some results regarding this comment in lines 169-184 which\nreference new main figure 3. Specifically, we report seasonal oxygen dynamics of\nisopycnals directly below the mixed layer in new figure 3 and found that oxygen\nsaturation is ~95% during deep mixing in March compared to ~108% in August on\naverage.\nLine 179: Order by depth: upper mixed layer, SOM, DCM\nThe order of the depths has been fixed. Line 204\nLine 183: The abbreviations are getting excessive here. I think you can write out the\nword surface. Also, just write out base of the mixed layer. Excessive abbreviation are a\nbarrier to reader understanding.\nThe abbreviations for upper mixed layer, surface, and base of the mixed layer have\nbeen removed and replaced with the actual word throughout the text to avoid reader\nconfusion. However, abbreviations are kept in the figures as abbreviated due to size\nconstraints, but are defined in the figure legends.\nLine 197 etc: using metagenomic data, (Fuchsman and Hays, 2023; Fuchsman et al.,\n2023) clearly show the same Prochlorococcus ecotypes in the mixed layer and right\nbelow the mixed, but different ecotypes dominating the DCM in the subtropical North\nAtlantic. Also some good information about cyanophage dynamics.\nThe relevant literature suggested has been added to the results (lines 228) and\ndiscussion regarding cyanophage dynamics (lines 372-374).\nLine 210: were. Past tense\nTense has been fixed (line 232)\nLine 219: I am not sure what sub-surface mixed layer peaks means. I mean, I figured it\nout, but maybe explain more clearly.\nThe sentence has been reworded and simplified to just “below the mixed layer” (line\n242-244)\nLine 228-230: Really you want primary production rates and bacterial production rates\nfor these analyses. Not cell numbers.\nThis is a valid point and we have attempted to address this by assessing the BATS\nhistorical primary and secondary production rates as suggested (see explanation\nabove). We still include the cell number results (lines 248-253) because we have this\ndata for the cruise and to contextualize the findings relative to the rate measurements\ndiscussed in lines previously.\nLine 254 and lines 268-274: There is usually an ammonium peak at the DCM or right\nbelow the peak of the DCM. So this is easily explained. You can see such an\nammonium peak in (Widner et al., 2018) in the Pacific, but there must be similar data\nfrom the Atlantic. I believe it is a typical feature in the ocean.\nWoodward and Rees (2001) Deep Sea Research Part II shows the ammonium peak in\nthe Atlantic. There is also Rees et al 2006 Deep Sea Research Part II.\nI think you can assume this feature is also present at BATS.\nWe start by noting that these regions are difficult to directly compare biogeochemically\nwith respect to the nutrients that are constraining productivity (as that constraint would\nchange nutrient accumulation and consumption). We secondarily comment that\naccumulations of nutrients (in this case ammonium) can result from many processes -\nnot the least of which is the biological supply of these nutrients through the actions of\nthe microbial loop or viral shunt.\nIn the case of the Sargasso, it is widely held that P-availability limits productivity (see\nLomas et al. 2010 Biogeosciences). This suggests then that the N supply could be\n(generally) sufficient. But the question arises as to the mechanism of that supply. In\nthis study we are providing data that support the theory that viruses may be playing an\nimportant role in the resupply of DON to heterotrophs which then respire that material\nand seem to return the ammonium to Prochlorococcus. We do not mean to argue that\nthere is no deep supply of ammonium. We point out that the intensity of amt\ntranscription does not simply directly increase with depth as Prochlorococcus\ncommunities get closer to that deep ammonium supply, but is instead peaking in the\nSOM.\nLine 259: lower than the mixed layer? Or the DCM?\nLowest at the SOM compared to all other measured depths (DCM, surface, base of\nmixed layer). The wording has been adjusted to clarify what we compared (line 265-\n268)\nLine 274: That is really too bad!\nAgreed\nLine 311: Also seen in (Fuchsman and Hays, 2023)\nThe observations in Fuchsman and Hays, 2023 have been included in Lines 378-379\nLine 344: viral isolates\nFixed – line 358\nLine 432: lol! I am sure you can find a paper than uses these criteria, which would be\nbetter than a webpage. Probably one of Dave Karl’s tomes. Anyway, fix this.\nKarl et al 2021 says “depths of upper mixed layer based on the density criterion of de\nBoyer Montegut et al. (2004),” so maybe track down that one.\nGot it! de Boyer Montégut et al 2004 has been added for the mixed layer depth method.\n(Line 460)\nLine 435: List the shallower depths first\nDone (line 463)\nLine 454-455: You already said how you calculated the mixed layer above.\nThe explanation has been removed from the section and the section above has been\nreferenced for BATS historical data processing. (lines 480-490)\nLine 478-480: Do you have a time estimate of how long it took to get the RNA from the\nNiskin bottles to the freezer? This is critical for determining quality.\nIt takes us <1h (often just 15min) to get the RNA from the Niskins to the freezer. We set\nup a pump system where samples were filtered directly from the collection bottles and\nthrough the Sterivex simultaneously (6 samples at a time), and only 3L were filtered per\nsample. For the 8a/8p timepoints, there were 8 samples per cast. For the 12a/4a/12p/4p\nsamples, there were only 4 samples collected per cast. The time from collection to\nfreezing has been added in the Methods in Line 515.\nLine 644: This sequence data needs to be submitted to NCBI SRA. The people at\n[NG1]\nJGI will do this for you. But it needs to be done. And you need to add a supplemental\ntable with all of the accession numbers and numbers of good quality reads.\nThe libraries have been uploaded to NCBI SRA and accession numbers added to\nSupplementary Table 4. The data regarding good quality reads has also been added to\nSupplementary Table 4. A sentence has been added to Line 683 to point the readers to\nthe information in the table.\nLine 644: The BATS bottle data should also be specifically listed out here.\nSentences (Line 470-497) to the Methods (BATS CTD data processing section) have\nbeen added to list out the specific BATS bottle and rate data used.\nLine 658: I also have a DOE CSP grant and was told to also include the award doi in\npublication. I think you should also be acknowledging the staff that helped with\nsequencing and sequence analysis. Please look at the directions related to your award.\nProject staff that helped with the CSP has now been included in the Acknowledgments\nsection (line 697)\nPlease put the supplemental figures and their figure captions into one combined word\ndocument!!!!!!!!!!!!!!!!!!!\nSupplemental figures and their captions will be submitted in one combined word\ndocument.\nSince this is now a Nature Communications Document, the authors could take a few of\nthe many supplemental figures and make them main document figures. I would\nrecommend moving Figure S2 (SOM data from BATS) and Figure S4 Prochlorococcus\necotypes. It clearly shows that the SOM is more similar to the mixed layer than to the\nDCM.\nAs suggested, we moved Figure S2 to main Figure 3. Figure S4 has been included in\nadditional panels in main Figure 4. Renumbering of the Figures has been done\naccordingly.\nBibliography\nFuchsman, C.A., Garcia Prieto, D., Hays, M.D., and Cram, J.A. (2023) Associations\nbetween picocyanobacterial ecotypes and cyanophage host genes across ocean basins\nand depth. PeerJ 11: e14924.\nFuchsman, C.A. and Hays, M.D. (2023) Increased cyanophage infection at the bottom\nof the euphotic zone, especially in the fall. Environ Microbiol 25: 3349–3363.\nWidner, B., Mordy, C.W., and Mulholland, M.R. (2018) Cyanate distribution and uptake\nabove and within the Eastern Tropical South Pacific oxygen deficient zone. Limnol\nOceanogr 63: S177–S192.\nReviewer #2 (Remarks to the Author):\nGilbert et al. is a study examining the role of viruses in the formation of SOMs in water\nat the BATS site. Using geochemistry, transcriptional activity, and cell counts over\ntimeseries they conclude that viral predation enhances oxygen production and NPP.\nThe manuscript is well written, and the approaches are adequately support the\nconclusions. There are no major issues with this study.\nWe thank the reviewer for their feedback and have addressed all specific issues in the\nresponses below.\nSpecific issues:\nLn 85 - Suggested re-wording to remove the repetition of \"by\" in this sentence.\nThe first “by” has been replaced with via to reduce repetition. (Line 80)\nLn 260 - Suggested change to: that were significantly\nThe wording was changed using this suggestion (Line 279)\nLn 272 - Are the strains in the SOM part of this group with constitutively high amt\ntranscription?\nIt is possible that we captured an ecotype at the SOM that may constitutively express\namt, however we see a mixture of different ecotypes (mainly, HLI and HLII, although\nHLII is more abundant relatively based on transcripts, see new Figure 4). The strains\nreferenced in the literature w/ constitutively high amt transcription are MED4 (HLI) and\nMIT9313 (LLIV). The LLIV ecotype was not detected in abundance at the SOM, and HLI\nis not as abundant at the SOM compared to HLII. We have included the ecotypes\nreferenced from the literature cited in the sentence regarding the constitutive expression\n(Line 292-293).\nLn 287 - Are there references that could be cited here to back up this assumption that\ntransporters are induced in the presence of their substrates?\nRefs 31 and 32 include evidence of this, however we removed the sentence in\nthis section to make this paragraph more concise.\nLn 432 – missing citation\nThe citation for the MLD definition has now been included (de Boyer Montégut et al\n2004) - Line 455\nLn 435 - This doesn't matter for understanding but this sentence may read more easily if\nall the layers are listed from either minimum to maximum (i.e. 5-40 m, 100-120 m, 50-60\nm) or max-min.\nReviewer 1 had the same comment, and so the depths are now ordered from minimum\nto maximum (Lines 458)\nLn 551 - Which Illumina instrument was used?\nNovaSeq S4 (same as the metaTs) - model used has been added to Line 582\nLn 558 - The recommendation for clustering on large-scales (>1,000s of sequences like\nyou have here), according to the ClusterGenomes github page, is to use anicalc and\naniclust in the CheckV distribution instead of ClusterGenomes.\nI would s anicalc and aniclust from CheckV and verify the ClusterGenomes clustering\naccurately clustered the large number of viral sequences from this study.\nBased on the suggestion, the dataset was run using anicalc/aniclust (same identity\nthresholds) from CheckV to compare to the ClusterGenomes results originally reported\nin the manuscript. We found that ClusterGenomes dereplicated those to 4921 vOTUs\n(1365 were > 10kb), aniclust/anicalc dereplicated to 4977 vOTUs (1368 were > 10kb).\nThe only difference in the vOTUs were the 56 that ClusterGenomes did not identify.\nFurther, ClusterGenomes, which uses nucmer from MUMmer package, is a global\naligner which is better for accuracy. Whereas anicalc/aniclust uses megablast which is\nfor fast local alignments and good enough for small genomes like viruses – hence\npreferred by the community for ease of use and efficiency. Ultimately, both tools use the\nsame calculations post alignment hence the same vOTUs identified by both tools; and\nwhile differences are expected, the vOTUs identified by ClusterGenomes are more\naccurate than those identified by anicalc/aniclust.\nReviewer #3 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports.\nThis is part of the Nature Communications initiative to facilitate training in peer review\nand to provide appropriate recognition for Early Career Researchers who co-review\nmanuscripts."}, {"round": 2, "reviewer_comments": {"reviewer_1": "This paper is much improved. As I said previously, this work is noteworthy for actually linking viral infection and\nbiogeochemistry. The results are excellent. I list out small problems below.\nDetails\nLine 68 Abstract: hmmm…. Usually people say that increased transcription of transporters indicates limitation. Here you say\nthe opposite. I might edit or cut this sentence.\n--The main text deals with this issue very well. Perhaps, in the abstract, expand the sentence to say elevated amt combined\nwith lower ntcA transcripts indicate a response to the presence of increased ammonium.\nLine 98: Change comma to period.\nLine 151: “The SOM during this study” – at first I thought you were referring to the SOM in the paper described in the\nprevious sentence. Perhaps “our study”\nLine 169: You work in scientific papers should be in the past tense. Identified\nLine 173: Indicated\nLine 188: correlated\nLine 190: measure is used awkwardly here\nLine 227-228: The sentence “A peak in Prochlorococcus HLI has been observed below the mixed layer in the Mediterranean\nSea.” Did that occur during a SOM? Yes, it did. See Haro-Moreno et al 2018 “Fine metagenomic profile of the\nMediterranean…” Table 1.\nLine 277-278: Diel cycling is reduced at the DCM in general. See Vislova et al 2019. “Diel oscillation of microbial gene\ntranscripts declines with depth in oligotrophic ocean waters”\nLines 311-313: This is nice.\nLines 394-396: And primary production!!!! Add in.\nLine 411: but Prochlorococcus always increases amt expression at dusk??? This is normal. Vislova et al 2019.\nLine 682: Raw meta-transcriptome and virome reads should be deposited at NCBI SRA. This is a community standard.\nIt is possible that Table 1 should be supplemental just do to the fact that it is so big.\nFigure 1c—red green color blind people can’t read this one.\nFig 4bc—same\nI know that red green color-blind people seem theoretical, but I have two in my lab. It is more common than you think.", "reviewer_2": "I feel all my comments were addressed adequately.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature\nCommunications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career\nResearchers who co-review manuscripts."}, "author_response": "Text has been changed to read \"Cruise data also showed Prochlorococcus nitrogen\nmetabolism transcripts consistent with increased responsiveness to remineralization activity by\nheterotrophs.\" We kept this text less specific to still fit in the abstract without leading to the\nawkward reading you point out.\nLine 98: Change comma to period.\nDone\nLine 151: “The SOM during this study” – at first I thought you were referring to the SOM in\nthe paper described in the previous sentence. Perhaps “our study”\nDone\nLine 169: You work in scientific papers should be in the past tense. Identified\nLine 173: Indicated\nLine 188: correlated\nLine 190: measure is used awkwardly here\nTenses changed and line 190 changed to \"Furthermore, the experiments that have the\nhighest oxygen saturation and most closely resemble a SOM also have the highest\nprimary and secondary production rates in the BATS climatology \" to remove the\nawkward use of 'measure'\nLine 227-228: The sentence “A peak in Prochlorococcus HLI has been observed below the\nmixed layer in the Mediterranean Sea.” Did that occur during a SOM? Yes, it did. See Haro-\nMoreno et al 2018 “Fine metagenomic profile of the Mediterranean…” Table 1.\nText changed from \"observed below the mixed layer\" to \"observed in a SOM\". The\nreference (Haro-Moreno et al 2018) has also been included at the end of the\nsentence.\nLine 277-278: Diel cycling is reduced at the DCM in general. See Vislova et al 2019. “Diel\noscillation of microbial gene transcripts declines with depth in oligotrophic ocean waters”\nWe agree with this comment - our point is that instead of monotonically decreasing\nwith depth in our study, the diel cycle in amt transcripts appears to have a higher daily max\nin the SOM than both the DCM and the surface.\nLines 311-313: This is nice.\nThank you.\nLines 394-396: And primary production!!!! Add in.\nPrimary production added to list.\nLine 411: but Prochlorococcus always increases amt expression at dusk??? This is normal.\nVislova et al 2019.\nWe agree with this point, with this sentence we just wanted to use an additional\npiece of evidence (the beam attenuation) to argue that the diel cycle in ammonium\ntransporters is coupled directly to community growth.\nLine 682: Raw meta-transcriptome and virome reads should be deposited at NCBI SRA.\nThis is a community standard.\nThe NCBI SRA Ids for have been included in the Data Availability Section as well as\nSupplementary Table 4 (lines 695 – 696).\nIt is possible that Table 1 should be supplemental just do to the fact that it is so big.\nTable 1 is now supplementary table 3 due to size constraints.\nFigure 1c—red green color blind people can’t read this one.\nFig 4bc—same\nI know that red green color-blind people seem theoretical, but I have two in my lab. It is\nmore common than you think.\nWe have adjusted the color schemes in Figure 1c and Fig 4bc to account for\nred/green color blindness."}]

Decision letter