Mozak neandertalaca povećan je s većom potrošnjom ugljikohidrata

Mozak neandertalaca povećan je s većom potrošnjom ugljikohidrata


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Prije otprilike milijun godina, mozak neandertalca udvostručio se u veličini za oko 200.000 godina, što je u evolucijskom smislu neznatan broj. Dugo se evolucija mozga pripisivala sve sofisticiranijoj upotrebi kamenih alata. Veći mozak dao je neandertalcima nove prednosti u lovu i traženju hrane. Ovi faktori dugo su poznati kao glavni razlozi za veći neandertalski mozak, ali najnovije istraživanje o ovoj temi istaklo je još jedan faktor u ovoj promjeni veličine mozga: potrošnju ugljikohidrata.

Nova studija objavljena u Zbornik radova Nacionalne akademije nauka (PNAS), koji je proučavao oralne mikrobiome i bakterije iz zuba neandertalaca i modernog čovjeka (prije Poljoprivredne revolucije prije 10.000 godina), baca novo svjetlo na to zašto se neandertalski mozak povećavao. Istraživači su otkrili da se hrana bogata škrobom i ugljikohidratima, konzumirana toliko često da je promijenila bakterije u njihovom tijelu, promijenila njihovo ponašanje i veličinu mozga.

"Mislimo da vidimo dokaze o zaista drevnom ponašanju koje je moglo biti dio encefalizacije - ili rasta ljudskog mozga", rekla je profesorica s Harvarda Christina Warinner. "To je dokaz novog izvora hrane koji su rani ljudi mogli iskoristiti u obliku korijena, škrobnog povrća i sjemenki." Brzo je naglasila da očito ljudska bića koja su bila dio ovog procesa nisu bila svjesna posljedica koje bi to imalo na njihov mozak.

Grauerovi uzorci gorila u Kraljevskom muzeju za centralnu Afriku u Tervurenu (Belgija) pokazuju tipične naslage zubnog kamenca na zubima koji su tamno obojeni, vjerovatno kao rezultat njihove hrane biljojeda, koja bi uključivala puno škroba i ugljikohidrata. (Katerina Guschanski / Kraljevski muzej za centralnu Afriku )

Neandertalski mozak, zubni plak i oralni mikrobiom

Najnovija studija mozga neandertalaca bila je veliki poduhvat, koji se sastojao od multidisciplinarnog međunarodnog istraživačkog tima od 50 naučnika iz 13 zemalja i 41 institucije. Tim su prvenstveno vodili istraživači sa Instituta Max Planck za nauku o ljudskoj istoriji, Njemačka i Univerziteta Harvard.

Studija je trajala više od 7 godina dok je tim mukotrpno analizirao fosilizirane zubne naslage neandertalaca i kasnog pleistocena kod modernih ljudi koji su živjeli u posljednjih 100.000 godina, te ih usporedio s onima divljih šimpanzi, gorila i majmuna urlika.

  • Studija pokazuje da su neandertalci imali sposobnost proizvesti i razumjeti govor
  • Spektakularna nauka! Mini neandertalski mozgovi uzgojeni u laboratoriji mogli bi objasniti po čemu se ljudi razlikuju

"Uspjeli smo pokazati da se bakterijska DNK iz oralnog mikrobioma čuva najmanje dva puta duže nego što se mislilo", rekao je J. A. F. Yates. Bio je vodeći autor studije i trenutno je doktorand na Institutu Max Planck za nauku o ljudskoj istoriji. "Alati i tehnike razvijeni u ovoj studiji otvaraju nove mogućnosti za odgovore na temeljna pitanja u mikrobnoj arheologiji i omogućit će šire istraživanje intimnog odnosa između ljudi i njihovog mikrobioma."

Oralni mikrobiom jedan je od ključnih pokazatelja ljudskog zdravlja, biologije i bolesti. Međutim, vrlo se malo zna o njegovoj ulozi u evoluciji ili raznolikosti u različitim topografijama. Osim toga, pronalaženje milijardi DNK sekvenci i fragmenata, starih stotinama hiljada godina, složen je i glomazan proces.

Arheogenetičari moraju sastaviti slomljene fragmente drevnih genoma, a zatim, koristeći hi-tech podatke i tehnologiju, pokušavaju razumjeti davno mrtve bakterijske zajednice. Imali su sreću sa rekonstrukcijom 100.000 godina starog mikrobioma neandertalca iz pećine Pešturina u Srbiji, udvostručivši starost prethodno najstarijeg rekonstruisanog oralnog mikrobioma.

Krupni plan lobanje aboridžinskog neandertalskog pećinskog čovjeka na kojem se jasno vide zubi i zubni plak, koji je korišten za razumijevanje oralnog mikrobioma i konzumacije neandertalskih ugljikohidrata. ( gerasimov174 / Adobe Stock)

Mozak neandertalaca i bakterije zuba loše istraženi

Drugi izazov je što je ovo područje istraživanja iznenađujuće slabo istraženo u smislu imenovanja miliona bakterija koje žive u našim ustima. Većina oralnih mikrobioma odgovorna je za vitalne funkcije u ljudskim ustima, uključujući zdrave desni i zube. Ipak, većina ovih bakterija ostaje neimenovana, što predstavlja temeljne izazove za suvremene istraživače.

Prema istraživanju, zajednice bakterija u ustima modernih ljudi prije poljoprivrede i neandertalaca jako su ličile jedna na drugu. Konkretno, moderni ljudi i neandertalci imali su neobičnu grupu Streptococcus bakterija u ustima. Streptococcus ima jedinstvenu sposobnost vezanja za obilni enzim u ljudskoj slini koji se naziva amilaza, enzim koji katalizira hidrolizu škroba u šećer.

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Bakterija koja konzumira šećer pronađena je u DNK plaka neandertalaca i modernog čovjeka, što ukazuje na određenu potrošnju škroba. Šimpanze, s druge strane, nemaju streptokokne bakterije na zubima. Osim toga, streptokok prisutnost i kod neandertalaca i kod ranih ljudi ukazuje na nasljeđivanje mikroba od zajedničkih predaka, potencijalno prije 600.000 godina.

Porodica neandertalaca ili ranih homo sapiensa koji kuhaju. Najnovije istraživanje pokazuje da na jelovniku nije bilo samo meso, već i povećane količine ugljikohidrata, što je doprinijelo povećanju veličine mozga. ( Gorodenkoff / Adobe Stock)

Ljudska evolucija i mikrobiomi

Posljedice toga, u proučavanju ljudske evolucije, duboke su i četverostruke.

  • Mali pad stope plodnosti mogao je dovesti do izumiranja neandertalaca
  • Neandertalci su definitivno imali dijetu zasnovanu na mesu: opovrgnute tvrdnje o biljnoj i kanibalskoj ishrani

Prvo, teorija velikog proširenja mozga, koja je bila usredotočena na razvoj kamenih alata i konzumaciju mesa, proširila je svoj opseg za buduća istraživanja.

Drugo, kako kaže Christina Warriner sa Sveučilišta Harvard, molekularna arheologinja i koautorica u studiji, "... ovo potiskuje važnost škroba u prehrani unatrag u prošlost."

Treće, prisustvo enzima amilaze, koji pomaže efikasnosti probave kuhane hrane, također ukazuje na to da je kuhanje postalo uobičajeno i rasprostranjeno prije oko 600.000 godina. To pomaže raspršiti mišljenje da je kuhanje, kakvo poznajemo, bilo sinonim samo za Poljoprivrednu revoluciju, koja je mnogo noviji fenomen. Ubuduće se postavlja pitanje je li kuhanje bilo dio ekspanzije velikog mozga prije otprilike 2 milijuna godina, ali žiri još uvijek ne razmišlja o tome.

Konačno, studija je pomogla poboljšati naše znanje o mikrobiomima i učiniti njihovu studiju ozbiljnom prijedlogom za sadašnje i buduće povjesničare. Kao što Warriner jezgrovito kaže: "To pokazuje da naš mikrobiom kodira vrijedne informacije o našoj evoluciji koje nam ponekad daju nagovještaje o stvarima koje inače uopće ne ostavljaju tragove."


Neželjeno: Istorija Marka Bittmana zašto jedemo lošu hranu

Mark Bittman piše kako kuha: Sastojci su zdravi, priprema elegantno jednostavna, a rezultati njeguju u najboljem smislu riječi. On se tamo nikad ne napreže i ne trudi se impresionirati, ali odlazite puni, zadovoljni, okrepljeni.

Iz njegovog magnum opusa, Kako sve skuvati, i njegovih mnogih pratilaca u kuharicama, do njegovih recepata The New York Times, u svojim esejima o politici hrane, Bittman je razvio povjetarac koji prikriva težinu politike i ekonomije koja okružuje proizvodnju i konzumiranje hrane. In Životinje, povrće, smeće, njegova posljednja knjiga, nudi nam svoj najopsežniji napad na korporativne snage koje upravljaju našom hranom, prateći evoluciju uzgoja i potrošnje od iskonskih do modernih vremena i razvijajući ono što je vjerojatno njegov najradikalniji i najiskreniji argument do sada o tome kako se pozabaviti našim savremene kulture hrane i brojne bolesti. No, i dalje se lagano spušta, prokulice su dovoljno dobrog ukusa da sa zadovoljstvom možete otići na nekoliko sekundi.

Bittman počinje Životinje, povrće, smeće sa ranim homininima. Kako su ti ljudski preci naučili hodati uspravno, počeli su tražiti hranu po većim površinama i loviti s relativno lakoćom. Bittman primjećuje da su također počeli razvijati fleksibilniju prehranu: & ldquoa raznoliko voće, lišće, orašasti plodovi i životinje, uključujući insekte, ptice, mekušce, rakove, kornjače, male životinje i helliprabitove, te ribe. & Rdquo Na kraju, uz povećanje hranjivosti novom prehranom, ubrzo su naučili kako brže pratiti plijen (što je bilo lakše učiniti u grupama i tako proizveli više društvenog ponašanja) i kuhati na vatri.

S više hranjivih tvari i naprednijim metodama skupljanja i kuhanja hrane, rani hominini i rsquo & ldquo već veliki mozgovi postali su veći. & Rdquo Bez žice da jedu & ldquo ono što možemo, kad možemo, & rdquo imali su dijetu koja se razlikovala od mjesta do mjesta: & ldquoNeki ljudi imali su visoku prehranu masti i bjelančevina, a neki su imali dijetu u kojoj su dominirali ugljikohidrati. & rdquo No, unatoč tim razlikama, kulture hrane i prehrane u nastajanju imale su jedno zajedničko. Epoha lova i sakupljanja proizvela je ldquo razdoblje veće dugovječnosti i općeg zdravlja nego u gotovo svakom drugom razdoblju prije ili poslije. & Rdquo Na kraju je proizvelo i novi trik: kako ostati na jednom mjestu i uzgajati usjeve čiji bi se višak mogao pohraniti.

Taj prijelaz iz lova i sakupljanja u poljoprivredu bio je dobrodošao na mnogo načina, ali imao je svoju cijenu, piše Bittman. Da, podržavao je veće stanovništvo, ali prehrana je postala monotona i manje hranjiva, životni vijek se smanjio, a radno vrijeme se povećalo. Bittman nije prvi koji je izneo ovaj argument. Jared Diamond je sjećanje nazvao poljoprivredu najvećom greškom u ljudskoj istoriji, pa Bittman ne odustaje od toga, prihvaćajući da sada živimo na planeti gdje je hrana nešto što uzgajamo, a ne nešto što lovimo ili skupljamo.

Za Bittmana, središnja drama ove priče počinje tijekom prošlog stoljeća, budući da su poljoprivreda i prerada hrane postale masovna industrija, a kako smo prešli s dvije vrste hrane (biljke i životinje) na preplavljivanje novom trećom vrstom & mdashone to je bilo ldquomore slično otrovu. & rdquo Ove & ldquoinženjerske jestive tvari, jedva prepoznatljive kao proizvodi zemlje, obično se nazivaju & lsquojunk. & rsquo & rdquo

Ova nezdrava hrana stvorila je, tvrdi Bittman, krizu javnog zdravstva koja umanjuje živote možda polovici svih ljudi. & Rdquo Svojom ovisnošću o poljoprivredi koja se ldquokoncentrira na maksimiziranje prinosa najisplativijih usjeva, & rdquo nanijela je & ldquomore štetu Zemlja nego iskopavanje traka, urbanizacija, čak i vađenje fosilnih goriva. & rdquo


Krivite drevnu promjenu klime.

Između 2,6 i 2,5 miliona godina, Zemlja se znatno zagrijala i osušila. Prije te klimatske promjene, naši daleki ljudski preci kolektivno poznati kao hominini— prehranili su se uglavnom plodovima, lišćem, sjemenkama, cvijećem, korom i gomoljima. Kako je temperatura rasla, bujne šume su se smanjivale, a veliki travnjaci napredovali. Kako je zelenih biljaka postajalo sve manje, evolucijski pritisak primorao je prve ljude da pronađu nove izvore energije.

Savane travnjaka koje su se prostirale Afrikom podržavale su sve veći broj biljojeda na ispaši. Arheolozi su pronašli velike kosti biljojeda od prije 2,5 miliona godina sa prepoznatljivim tragovima izrezanih alata od sirovog kamena. Naši stari preci hominini još uvijek nisu bili sposobni lovci, ali su vjerovatno očistili meso s palih trupova.

“Više trava znači više životinja na ispaši, a više mrtvih pasa znači više mesa, ” kaže Marta Zaraska, autorica Meathooked: Istorija i nauka naše opsesije mesom od 2,5 miliona godina.

Nakon što su ljudi prešli na čak i povremeno konzumiranje mesa, nije trebalo mnogo vremena da postane glavni dio naše prehrane. Zaraska kaže da postoje brojni arheološki dokazi da je prije 2 miliona godina prvi Homo vrste su redovno jele meso redovno.

Neandertalci love zebru za hranu.

Peter Bischoff/Getty Images


Kako je prehrana oblikovala našu prošlost i definira našu budućnost, kaže Mark Bittman

Razni tacosi iz Distrikta Taco u Washingtonu, Virdžiniji i Philadelphiji. „Nismo ovdje ako nije zbog hrane. Dakle, hrana je odrednica načina na koji koristimo zemlju. Tu mi živimo ", kaže autor Mark Bittman. Fotografija: Brandon Dewey Photography.

Hrana je igrala važnu ulogu u ljudskoj istoriji i evoluciji. Unoseći više i kvalitetnijih kalorija, naš mozak je postao veći, a mi smo postali pametniji i pažljiviji u pronalaženju i uzgoju hrane.

Putovanje hranom i potreba za jelom utjecali su na sve, od ropstva i kolonijalizma, do gladi i genocida. Sada industrijska poljoprivreda prijeti javnom zdravlju i pogoršava klimatske promjene.

Joanthan Bastian iz KCRW -a razgovara sa poznatim piscem o hrani Markom Bittmanom o njegovoj posljednjoj knjizi "Životinje, povrće, smeće: Povijest hrane, od održive do samoubilačke". Gledaju kako je hrana oblikovala našu prošlost i možemo li utjecati na nju u budućnosti.

Slijedeći odlomci intervjua su skraćeni i uređeni radi jasnoće.

KCRW: U svojoj knjizi koristite hranu kao okvir za povratak kroz vrijeme i govorite o tome kako se ljudi razvijaju. Kako ste mislili da bi to bio važan način da shvatimo dokle smo došli kao ljudsko društvo?

Mark Bittman: „Zašto ne hranu? To je najvažnija stvar koja postoji. Mogli biste se raspravljati o hrani u odnosu na kisik. Ali očito, nismo ovdje ako nije zbog hrane. Dakle, hrana je odrednica načina na koji koristimo zemlju. Tu mi živimo. ... Rad je počeo kao poljoprivredni rad.

Mislim da se to dogodilo nakon godina govorenja: "Ne možete popraviti društvo bez popravljanja sistema ishrane, i ne možete popraviti sistem prehrane bez popravljanja društva", i govoreći o vezama između hrane i svega ostalog. Sinulo mi je da je to oduvijek bilo tako, da je hrana sve pokrenula i da nikada nije prestala biti jedan od najmoćnijih utjecaja. ”

Započinjete jedno od ranih poglavlja s „petljom povratne informacije hrana-mozak“. Šta je to?

„U osnovi opisuje proces kojim smo izašli iz drveća. Počeli smo jesti raznolikiju prehranu. Nitko to zapravo ne zna, ali pretpostavlja se da smo jedući više i kvalitetnijih kalorija naš mozak postao veći. I kako nam je mozak rastao, bili smo sposobni biti pametniji i pažljiviji.

Uspjeli smo pronaći više hrane, postali smo bolji u pronalaženju hrane. I kako smo postajali sve bolji u pronalaženju hrane, naš mozak je postajao sve veći. I taj proces se nastavio par stotina hiljada godina, sve dok nismo ... nadjačali neandertalce i postali primarna vrsta homo sapiens koji smo. ”

Možete li proširiti ideju o unosu kalorija i veličini mozga?

“Nisam siguran da se radi o količini kalorija koliko o kvaliteti kalorija. ... Došlo je do brojnih promjena u našim tijelima u odnosu na tijela naših majmunolikih predaka. Te su životinje potrošile mnogo vremena na žvakanje i puno vremena pretvarajući zelene i drvenaste tvari u probavljivu hranu koja se tada mogla pretvoriti u aminokiseline i proteine.

Kad smo sišli s drveća, a posebno kad smo počeli loviti, počeli smo jesti izravnije. Dakle, hrana koja je bila veći izvor proteina. Tako da mislim da se mnogo radi o konzumaciji proteina, to je većoj veličini mozga ili akutnijim sposobnostima razmišljanja. I to se samo nastavilo, nastavilo i nastavilo godinama.

Na kraju smo mogli bolje loviti. Na kraju smo uspeli da kuvamo. A to je značilo da smo imali na raspolaganju još više izvora hrane, jer je mnogo hrane za koju se činilo da je jestiva jako, jako teško žvakati, ili vrlo, vrlo probavljiva, osim ako je kuhana. Dakle, kontrola vatre bila je ogromna stvar u određivanju smjera naše dijete. I dijeta je općenito zahtijevala, posebno do pojave poljoprivrede, sve bolje smjerove. ”

FOTO: Mark Bittman je novinar o hrani, bivši kolumnista New York Timesa i autor knjige "Životinje, povrće, smeće: istorija hrane, od održive do samoubilačke". Fotografija: Jim Henkens

Odakle vodi priča o ovim ranim agrarnim društvima i poljoprivredi koji su se raširili po cijelom svijetu?

“Vratit ću se na formiranje poljoprivrede i njenu odgovornost za formiranje civilizacija. ... Kada je postojala poljoprivreda, to je postalo višak. A kad je došlo do viška, počeli su postajati ljudi čiji poslovi nisu bili poljoprivrednici. Do tada zaista nije bilo nikoga čiji posao nije imao veze s hranom.

Ali kad je bilo viška, mogli ste imati svećenike, graditelje, računovođe, pisce, političare, menadžere, trgovce i sve stvari koje sada smatramo zanimanjima ili poslovima. To je velika promjena. A činjenica da ste počeli uzgajati hranu i donositi zakone i civilizaciju započela je prije 10.000 godina, a možda se konsolidirala prije 2000 godina. To je bio veliki, veliki skok.

. Sljedeća stvar koja posebno zanima Sjeverne Amerikance je 13. do 16. vijek. Mislim da je najlakši način da se to objasni tako da se kaže da je potrebno više zemlje za prehranu ljudi koji ovise o životinjskim proizvodima nego za ishranu ljudi koji su više orijentirani na vegetarijanstvo.

Tako se veća populacija Azije uvelike objašnjava činjenicom da je u Aziji bilo više kultura ovisnih o biljkama nego u Europi. Tehnologija je bila jednako napredna. Zapravo, Kinezi su uplovili u Afriku, što je mnogo duže putovanje, mnogo prije nego što su Evropljani plovili Sjevernom Amerikom.

No, na neki način, pritisci stanovništva, trgovine, kapitalizma i nove ekonomije 15., a posebno 16. stoljeća u Europi zaista su forsirali to pitanje i natjerali Europljane da istražuju i traže novu zemlju, poljoprivredu i druge razloge, takođe. Ali prvenstveno, ili barem vrlo važno, zemljišta za poljoprivredu. Možete samo zamisliti zaprepaštenje Europljana kada su počeli istraživati ​​Sjevernu Ameriku i vidjeli veličinu i bogatstvo ovog kontinenta, te relativno malu populaciju autohtonog stanovništva ovdje. I nažalost, autohtoni narod koji je uspio biti osvojen kako bi ga Evropljani preuzeli.

Ali mnogo toga se odnosilo i na poljoprivredu. Europljani donose svoje poljoprivredne sisteme ovdje, svoje načine posjedovanja zemlje ovdje, svoje načine podjele zemljišta i svoju spremnost da kradu zemlju od drugih ljudi i ubijaju ako to moraju učiniti. To je bila sva priča iz 15. i 16. stoljeća, i to se nastavilo. Kao što znamo, to se nastavlja i sada, ali to je bio temelj ove zemlje, posebno. ”

Gdje vidimo da nas priča dalje vodi, posebno u Sjedinjenim Državama?

“Mislim da se najznačajnija stvar, jedna od ključnih stvari u Sjedinjenim Državama koje su se sada dogodile u razdoblju nakon građanskog rata. . 1862., usred građanskog rata, prvi put je donesen Zakon o imanju. … Cijelo zemljište zapadno od Apalača ustupljeno je bijelim muškarcima i željezničkim kompanijama, koje su, naravno, vodili i bijeli muškarci. No, zemlja se dijelila u relativno malim komadima - 160, 320 ili 640 jutara zemlje u osnovi je davano onima koji su htjeli napustiti Istok ili su htjeli napustiti Europu i postati poljoprivrednici. . To je bila rana odrednica bogatstva u Sjedinjenim Državama. I vlasništvo nad zemljom, očito, povezano je s bogatstvom, a činjenica da je zemlja ukradena od starosjedilaca i davana uglavnom bijelcima bila je ogroman prijenos bogatstva, i to ono što utječe na način na koji danas definiramo bogatstvo u Sjedinjenim Državama.

Podrazumijeva se da nikada nije bilo reparacija za milione Afrikanaca koji su ovdje dovedeni protiv njihove volje i porobljeni. Bilo je nekih obećanja danim slobodnim ljudima, bivšim robovima, o davanju zemlje. Rekonstrukcija je također mnogo obećavala o tome da će ovu zemlju učiniti ravnopravnijom. Ali ta obećanja su iznevjerena.

Išli smo od 1860. do sada, a da se nismo bavili pitanjem ko dobija zemlju za obrađivanje. Ono što smo vidjeli u međuvremenu je konsolidacija tog zemljišta koje je ustupila savezna vlada, konsolidacija zemljišta koje je bilo u vlasništvu bijelaca, u velikim dijelom korporacije u vlasništvu bijelaca.

Ako želite govoriti o rješavanju nejednakosti u Sjedinjenim Državama danas, morate razgovarati o rješavanju pitanja ko obrađuje zemlju, ko posjeduje zemlju i koji su njihovi ciljevi u obrađivanju zemlje. Sada smo na mjestu gdje možete vidjeti zašto mislim da je hrana tako odrednica onoga što se događa u društvu.

Nismo čak ni došli do toga da spominjemo javnozdravstvena pitanja koja se vrte oko hrane, ili pitanja pravičnosti, ili pristupačnosti. Još uvijek govorimo samo o zemljištu i poljoprivredi, a već govorimo o odrednicama kako naša zemlja trenutno izgleda. ”

Dakle, čak i u tom ranijem razdoblju američke povijesti, činjenica da su zemlju kontrolirali prvenstveno bijelci stvorila je ovu prirodnu podjelu hrane. Postojali su različiti načini distribucije hrane, odnosno načina na koji je plasirana. Možete li to iskoristiti kao odskočnu dasku za razgovor o nekim od ovih nejednakosti?

“Poljoprivreda se transformirala iz djelatnosti u kojoj su ljudi uzgajali hranu za sebe, svoje susjede, svoje regije - u djelatnost u kojoj su uzgajali hranu za transport i prodaju na drugom mjestu. A to se počelo događati rano. Izgradnja kanala Erie i prve pruge, a sve je to omogućilo.

Počinjete vidjeti kako poljoprivredno zemljište od uzgoja raznih usjeva prelazi u… robne usjeve. I robni usjevi su ono što je savezna vlada ohrabrivala, podržavala, pa čak i subvencionirala prije Prvog svjetskog rata, ali posebno početkom Prvog svjetskog rata. A ti robni usjevi zapravo nisu hrana za ljude, oni su hrana za industriju.

Dakle, ekstremni primjer je uzgoj kukuruza za etanol. Manje ekstremni, ali još uvijek izraziti primjeri su uzgoj hrane, uzgoj kukuruza za ishranu životinja, koji se zatim uzgajaju industrijski. Ili još gore, po mom mišljenju, uzgoj hrane koji se pretvara u hiperprerađenu hranu, koja se jedva kvalificira kao hrana i koja. trova ili razboli veliki postotak našeg današnjeg stanovništva. I, naravno, postotak stanovništva koje je najosjetljivije da se razboli marketingom nezdrave hrane su ljudi s manje novca. ”

Možete li govoriti o velikoj proizvodnji i prodaji prerađenog šećera i kako je poticaj prehrane s niskim udjelom masti proizveo velike zdravstvene probleme?

„U 20. stoljeću upravo je došlo do pretvaranja hrane u prehrambene proizvode u velikoj mjeri. Mnogi proizvodi koje smatramo hranom zapravo su izmišljeni u 20. stoljeću. Ne govorim samo o Twinkies-u, već o smrznutim večerama i konzerviranim juhama i nizu drugih stvari, do te mjere da je prema nekim procjenama 60% naših kalorija sada u obliku ultra prerađene hrane. Pod ultra prerađenom hranom mislim na hranu koju niste mogli sami napraviti. Hrana napravljena od sastojaka kojih nema u ničijoj kuhinji. Hrana koju naše bake ne bi prepoznale.

Dakle, šećer je svakako veliki dio toga. A šećer je vjerojatno najveći krivac za izazivanje kronične bolesti povezane s ishranom, koja je najveći ubojica u našoj zemlji, i… mnogo veća od COVID-a. Ali visoko prerađeni ugljikohidrati svih vrsta su loši za nas. I svake godine ima sve više prehrambenih proizvoda, tvari sličnih namirnicama, kako god ih htjeli nazvati, neidentificiranih predmeta nalik hrani ... i svake godine naše stope dijabetesa rastu, stope raka raste, naša prehrana je povezana bolesti rastu.

… COVID je ubio oko 300.000 Amerikanaca 2020. To prepoznajemo kao krizu. Suočili smo se s tim, s obzirom na ograničenja administracije, najbolje što smo mogli ... ali 1,5 do 1,7 miliona Amerikanaca umire od hronične bolesti povezane s ishranom. Ovo je broj Nacionalnog instituta za zdravlje. I to ne nazivamo krizom. Iz nekog razloga, spremni smo živjeti s tim. I ako mogu utjecati na taj broj, na način na koji razmišljamo o tom broju i kažemo, ovdje imamo krizu u prehrani čiji je temelj zaista u poljoprivredi, jer možemo jesti samo ono što proizvedemo. A mi ljudi nemamo kontrolu nad onim što se proizvodi, prerađuje i prodaje. Imamo vrlo malo kontrole nad našom ishranom. To se mora promijeniti. A to su velike stvari. To nije poput "Kupujte na vašoj farmi", iako je to dobra ideja. To je kao da nam je potrebna temeljna promjena u načinu razmišljanja o hrani. ”

Podržite KCRW - vaš svakodnevni život.

KCRW stoji iza naše misije da služimo našoj zajednici na sve načine na koje možemo u ovom teškom vremenu. Ovdje smo da vam pružimo lokalne vijesti, informacije o javnom zdravlju, muziku za vaš duh i kulturnu povezanost. Budite u toku i prijavite se za naše biltene. I, ako ste u ovom trenutku u mogućnosti podržati naše napore, razmislite o doniranju.


Diskusija

TLC kao apsolutno mjerenje vezano za respiratorni volumen može se koristiti za rješavanje pitanja respiratornih i energetskih potreba kod modernog čovjeka 44,45, a potencijalno i kod fosilnih hominina 9,35.

Međutim, iako se vrijednosti TLC -a dobivaju jednostavnom tehnikom u bolničkim subjektima (kao u Bellemareovoj studiji 44), veći je izazov kada se bavimo fosilnim zapisom. To je zato što TLC možemo zaključiti samo iz varijabli izmjerenih u pojedinim elementima grudnog koša, kao što su rebra i kralješci. S tim u vezi, naši rezultati su pionirski u pokazivanju da se pojedinačna veličina rebara (procijenjena kroz TVA_sml, TVC i CS) može povezati s TLC. Također smo specificirali da, iako je naše 3D mjerenje (CS) više povezano s TLC od tradicionalnog mjernog TVC -a za rebra 3-10, tuberkulozno -ventralni luk (TVA_sml) je još informativniji o TLC -u. To je vjerojatno uzrokovano činjenicom da TVA bilježi informacije o mediolateralnoj širini i opsegu pluća, dok TVC snima samo anteroposteriornu veličinu, što mora utjecati i na CS. Osim toga, specificiramo da je veličina središnjih donjih rebara više povezana s TLC -om nego veličina gornjih rebara (slika 1). To je u skladu s nedavnim istraživanjima koja pokazuju da je veličina donjeg dijela grudnog koša više povezana s funkcionalnom veličinom, shvaćenom kao povećanje veličine od maksimalnog izdisaja do maksimalne inspiracije 42.

Naši rezultati za neandertalce pokazuju da TLC predstavlja apsolutne vrijednosti koje su veće nego u odgovarajućim ljudskim kolegama (Tablica 3). Kebara 2, mužjak neandertalca iz Izraela, pokazuje prosječnu vrijednost od 9,04 l TLC -a, što je statistički veće od našeg uzorka muškaraca (prosjek = 7,20 l) i onog iz Bellemare i sur. 44 (srednja vrijednost = 6,27 l). Naše procjene za Tabun 1, ženu neandertalca iz Izraela, dale su srednju vrijednost od 5,85 l, što je statistički veće od našeg uzorka žena (prosjek = 4,85 l) i prosjek Bellemare et al. 44 (srednja vrijednost = 4,81 l). Treba napomenuti da je muški Kebara 2 TLC bio 54% veći od vrijednosti za ženku Tabun 1. Činjenica da je ovaj postotak nešto veći kod neandertalaca nego u našem uzorku modernog čovjeka (oko 48%, vidi gore) mogla bi biti rezultat razlika u tjelesnoj građi, jer Kebara ima veću mršavu masu u odnosu na Tabun 1 od naših muških modernih ljudi u odnosu na naše moderne ženke (Tabela 3). Rebro El Sidrón SD-1450 također pruža uvid u neandertalski TLC, a budući da je statistički veći od našeg uzorka muškaraca, vjerojatno je da je pripadao muškoj jedinci.

Važno je napomenuti da bi, da smo pokušali procijeniti TLC vrijednosti ovih fosilnih uzoraka koristeći druge varijable (poput stasa) iz standardnih ljudskih jednadžbi, Tabun 1 TLC bio procijenjen na 4,67 l, 4,50 l i 4,91 l koristeći formule iz Crappo et al. 46, Roca i dr. 47 i Quanjer i dr. 48, respektivno. Da smo koristili standardne ljudske jednadžbe za procjenu Kebara 2 TLC vrijednosti, dobili bismo vrijednosti od 6,18 l, 6,20 l i 6,36 l koristeći formule iz Quanjera i sur. 48, Cordero i dr. 49 i Neder i dr. 50, respektivno. Stoga, i Kebara 2 i Tabun 1 predstavljaju mnogo veće vrijednosti TLC koristeći naše jednadžbe nego kada se koriste standardne jednadžbe čovjeka. Budući da se koriste različite jednadžbe ovisno o spolu, ovu vrijednost nismo izračunali za hominine El Sidrón Neanderthal i ATD6, budući da njihov spol nije bio poznat.

Nedavni dokazi ukazuju na to da je velika TLC primijećena kod neandertalaca u usporedbi s modernim ljudima rezultat velikih rebara u središnjem donjem dijelu grudnog koša zajedno s leđnom orijentacijom poprečnih procesa kod neandertalaca u usporedbi s modernim ljudima, uzrokujući mediolateralno širenje grudnog koša 18 , 20. Ova morfologija grudnog koša (slika 3), u kombinaciji s našim rezultatima TLC -a za neandertalce, konzistentna je s velikim unosom kisika za održavanje očekivane visoke DEE koju su predložili prethodni autori 9,35,51. Taj veliki DEE mora biti uzrokovan njihovim velikim mozgom (slika 3, tablica 3) i velikom mršavom tjelesnom masom (tablica 3), ali alternativna objašnjenja poput mogućnosti da su neandertalci imali velika utroba (jetra i mokraćni sustav) neophodni za obradu velikih količine mesa, također se može povezati s visokim DEE 52.

a Oblik grudnog koša i pluća u frontalnom pogledu kod modernih ljudi i neandertalaca i s njima povezani mozak u bočnom pogledu. Neandertalski grudni koš i lobanja pripadaju neandertalcima Kebara 25 i Guattari. Moderni ljudski prsni koš i lubanja pripadaju u prosjeku četvorici modernih ljudi 82 i OI-2053. b Superponiranje u frontalnom pogledu na neandertalce i moderne ljudske rebra. c Superpozicija u kaudalnom pogledu na neandertalce i moderne ljudske rebra

Iako postoji slaganje oko velike veličine grudnog koša neandertalca 14,15,16,17,18,19,20, nije tako jasno jesu li njihovi grudni koš veći zbog tjelesne mase ili stasa 35. Na primjer, procjene respiratornog područja neandertalca Shanidar 3 rebra 8 ukazuju na to da je to bilo proporcionalno njegovoj tjelesnoj masi, ali da je respiratorno područje Kebara 2 rebra 8 bilo relativno veće za njegovu tjelesnu masu 35. S tim u vezi, naši rezultati mogu sugerirati da su i Kebara 2 i Tabun 1 predstavili veći omjer TLC/M od naših modernih referentnih uzoraka za ljude, što podržava Churchillovih 35 radova. Što se tiče toga da li neandertalci imaju veći TLC zbog svog rasta u odnosu na moderne ljude, naši rezultati podržavaju ovu tvrdnju budući da su TLC/S vrijednosti Kebara 2 i Tabun 1 jedinki bile (u prosjeku) veće od odgovarajućih uzoraka modernih ljudi. Činjenica da su oba neandertalca pokazala veće vrijednosti TLC/M i TLC/S u odnosu na naš uzorak modernog čovjeka mora biti povezana s njihovim velikim DEE.

However, some caution must be taken in the interpretation of these results since TLC/M and TLC/S ratio are based on estimates of stature and lean body mass in Neanderthals 9,35,51,53 and this could introduce some error in the ratios. Even when including this potential error, it is clear that Neanderthals’ thoraces were larger for their stature (Fig. 2), which would be consistent with previous research on ribcage/body size ratios based on rib size/humerus length 15 . It is also important to recall that lean body mass estimates were calculated applying fat-free mass percentages to the total Neanderthal body mass, which were taken from modern Inuit individuals 51,54,55 . Therefore, it is possible that the percentages for Neanderthals were different than those of Inuits. In addition to differences in fat-free mass percentages, there may also be differences in other tissues, such as brown adipose tissue. Although the role of this tissue in environmental adaptation is speculative, it is the only human tissue dedicated exclusively to heat production 56 . Body composition in Neanderthals is not the focus of our work and should be addressed in future research.

Regarding the evolutionary origin of the large Neanderthal TLC, H. heidelbergensis (likely potential ancestors of Neanderthals) are also thought to have large thoraces, both in absolute terms and perhaps relative to their stature as well 6,57 . However, the lack of literature on fossil remains of the costal skeleton makes it difficult to address this issue. Lower Pleistocene hominins from the Gran Dolina site (Burgos, Spain) are hypothetical ancestors of H. heidelbergensis (and thus Neanderthals) and are also thought to have large thoraces because of their long clavicles 6,30 . Whether H. antecessor is actually a species itself or represents an European branch of H. erectus/ergaster 34 , recent Bayesian analyses 58,59 suggest that H. antecessor belongs to a basal clade of modern human and Neanderthals, alongside other early Homo species such as H. erectus, ergaster and the recently discovered species named as H. naledi 60 . Therefore, H. antecessor could be used as an approach to test whether large bodied early Homo species already presented a large TLC.

Our results of estimated TLC based on ribs 7 and 10 yielded values of 5.28 l and 8.70 l for ATD6 hominins, respectively, which were larger than our comparative sample of female and male modern humans, respectively. In this case, we are not certain that these ribs belonged to the same individual, so we hypothesize here that ATD6–39 (the larger value) could represent a male rib, whereas ATD6–89+206 (the smaller value) could represent a female rib. If this is confirmed, we would see in ATD6 hominins the same evolutionary trend that we see in Neanderthals, males and females being larger (on average) than our modern human comparative sample. However, some caution should be taken because of the uncertainty in the composition of the ATD6 sample 31 . The TLC/M ratio for these hominins could not be calculated since body mass values are not available in the current literature due to the fact that this fossil site did not yield any remains of lower limbs that were well enough preserved to provide evidence of body mass 30 . Regarding stature, ATD6 hominins presented an average stature of 172.5 cm, which was larger than the average for Neanderthals 6,30,57 . The TLC/S ratio for ATD6 hominins using rib 7 was larger than the female average and larger than the male average using rib 10. This would support the possibility that ribs ATD6–89+206 and ATD6–39 are female and male ribs, respectively. It would also support what we found in Neanderthals, that is, that the large TLC relative to stature was beginning to be evident in the Lower Pleistocene of Europe, even when considering that ATD6 hominins presented larger statures than Neanderthals 6,30 .

Therefore, according to the evidence of TLC, if we accept that H. antecessor was in the basal clade of both Neanderthals and modern humans, we suggest here that a large ribcage relative to stature is present in the whole European hominin lineage (represented here by ATD6 hominins and Neanderthals). However, whether it is also present in other European hypothetically intermediate species such as H. heidelbergensis must be addressed in future research. The large ribcage of the European hominin lineage could be linked to the wide trunks proposed by previous authors for those species 6 , which would show an evolutionary trend towards Neanderthals, based on relative stature reduction and relative thorax size increase.

Regarding the adaptive significance of this evolutionary trend, it should be noted that in the Lower and Middle Pleistocene there is a trend towards large body sizes across most of the mammal clade, with herbivores showing a larger size increase than carnivores 61,62,63,64,65 . In carnivores, this size increase could be important for facilitating hunting tasks, whereas in herbivores it could be important for avoiding being preyed upon by carnivores. This general ecological rule could also apply to hominins and perhaps underlie the large body mass of Lower and Middle Pleistocene hominins, partially explaining their wide trunks 9 . Besides this general explanation, other more specific ones have been proposed: the stout (“short but massive”) Neanderthal body could be explained by the eco-geographical rules of Allen and Bergmann 66,67 , which could cause the shortening of distal limbs and the widening of the trunk observed in Neanderthals 1,2,3,4,5,6,7,8,9 . However, recent studies on bioenergetics show that Neanderthals inhabiting the same climatic conditions as modern humans present larger DEE than modern humans. This could be the result of the cost of maintaining heavy and highly muscled bodies with large brains (Fig. 3, Table 3) along with the need to exert muscular force in the accomplishment of subsistence tasks 9,35,36,51 . This larger muscle mass would have provided them with a greater thermogenic capacity and also greater insulation against cold compared to modern humans, which could be understood as an exaptation 9,35 . Future studies should include more Neanderthal ribs and also other hominin species not included here, such as H. heidelbergensis ili H. erectus, in order to expand the evolutionary framework.

Finally, even though physiological function must have been of evolutionary significance, caution should be used in assuming that an enlarged thorax was result of natural selection and was passed down as an adaptation to later European Pleistocene hominins. In particular, enhanced pulmonary function as modelled in modern human populations living at high altitudes shows that developmental processes have an important role in shaping the physiology of respiration and oxygen consumption 68,69,70,71,72 . Developmental factors also play an important role in determining thorax morphology. Here again, humans living at high altitudes from many different regions provide important data demonstrating this point, but the small sample sizes of hominin fossil assemblages make developmental factors difficult to test. The possibility that developmental processes contributed to the emergence of a large thorax and pulmonary capacity in early Pleistocene hominins of Europe and in later Neanderthals does not alter the results of this study.

Our work is, to our knowledge, the first successful attempt to estimate TLC in fossil hominins. We have found that Neanderthals presented around 20% larger lung capacities than modern humans, both absolutely and relative to their lean mass and stature. This could be caused by the large lean body mass of Neanderthals, coupled with their large brains and gut size (liver and urinary systems), contributing to their high DEE. Assuming that H. antecessor is in the basal clade of Neanderthals (which is still a heated debate), the trend towards large lung capacities could even be observed in the lower Pleistocene of ATD6. Finally, although we used a large sample of current Europeans to create a statistical model (controlled for stature and body mass) to calculate TLC in fossil hominins, future research should include broader samples from different modern humans populations. Those that present different limb proportions compared to Europeans and that could parallel Neanderthal body proportions (populations adapted to high altitudes and extreme low temperatures) are mostly necessary. In addition, future studies should make an effort to include early H. sapiens such as Cro-Magnon, Skhul or Abri Pataud.


Evolution Of Technology

By far the most interesting advancement in computers to me was the development of the “supercomper” called ATLAS. The University of Manchester developed ATLAS in the United Kingdom and it was officially authorized in 1962. This computer was unlike anything seen before it was ten times faster then any other computer built. There were many different changes in to the make the supercomputer so much faster and smarter. They changed their transistors from germanium to silicon.&hellip


CSIC reconstructs how Neanderthals grew, based on an El Sidrón child

How did Neanderthals grow? Does modern man develop in the same way as Homo neanderthalensis did? How does the size of the brain affect the development of the body? A study led by the Spanish National Research Council (CSIC) researcher, Antonio Rosas, has studied the fossil remains of a Neanderthal child's skeleton in order to establish whether there are differences between the growth of Neanderthals and that of sapiens.

According to the results of the article, which are published in Science, both species regulate their growth differently to adapt their energy consumption to their physical characteristics.

"Discerning the differences and similarities in growth patterns between Neanderthals and modern humans helps us better define our own history. Modern humans and Neanderthals emerged from a common recent ancestor, and this is manifested in a similar overall growth rate", explains CSIC researcher, Antonio Rosas, from Spain's National Natural Science Museum (MNCN). As fellow CSIC researcher Luis Ríos highlights, "Applying paediatric growth assessment methods, this Neanderthal child is no different to a modern-day child". The pattern of vertebral maturation and brain growth, as well as energy constraints during development, may have marked the anatomical shape of Neanderthals.

Neanderthals had a greater cranial capacity than today's humans. Neanderthal adults had an intracranial volume of 1,520 cubic centimetres, while that of modern adult man is 1,195 cubic centimetres. That of the Neanderthal child in the study had reached 1,330 cubic centimetres at the time of his death, in other words, 87.5% of the total reached at eight years of age. At that age, the development of a modern-day child's cranial capacity has already been fully completed.

"Developing a large brain involves significant energy expenditure and, consequently, this hinders the growth of other parts of the body. In sapiens, the development of the brain during childhood has a high energetic cost and, as a result, the development of the rest of the body slows down," Rosas explains.

Neanderthals and sapiens

The cost, in terms of energy, of anatomical growth of the modern brain is unusually high, especially during breastfeeding and during infancy, and this seems to require a slowing down of body growth. The growth and development of this juvenile Neanderthal matches the typical characteristics of human ontogeny, where there is a slow anatomical growth between weaning and puberty. This could compensate for the immense energy cost of developing such a large brain.

In fact, the skeleton and dentition of this Neanderthal present a physiology which is similar to that of a sapiens of the same age, except for the thorax area, which corresponds to a child between five and six years, in that it is less developed. "The growth of our Neanderthal child was not complete, probably due to energy saving", explains CSIC researcher Antonio Rosas.

The only divergent aspect in the growth of both species is the moment of maturation of the vertebral column. In all hominids, the cartilaginous joints of the middle thoracic vertebrae and the atlas are the last to fuse, but in this Neanderthal, fusion occurred about two years later than in modern humans.

"The delay of this fusion in the vertebral column may indicate that Neanderthals had a decoupling of certain aspects in the transition from infancy to the juvenile phase. Although the implications are unknown, this feature could be related to the characteristic enlarged shape of the Neanderthal torso, or slower brain growth", says Rosas.

The Neanderthal child

The protagonist of this study was 7.7 years old, weighed 26 kilos and measured 111 centimetres at the time of death. Although the genetic analyses failed to confirm the child's sex, the canine teeth and the sturdiness of the bones showed that it to be a male. 138 pieces, 30 of them teeth (including some milk teeth), and part of the skeleton- including some fragments of the skull from the individual- identified as El Sidrón J1, have recovered.

The researchers have been able to establish that our protagonist was right-handed and was already performing adult tasks, such as using his teeth as a third hand to handle skins and plant fibres. In addition, they know who his mother was, and that the child protagonist of this investigation had a younger brother in the group. Furthermore, this child was found to have suffered from enamel hypoplasia when he was two or three years old. Hypoplasia (white spots on the teeth, especially visible in the upper incisors), occurs when the teeth have less enamel than normal, the cause usually being malnutrition or disease.

Discovered in 1994, the El Sidrón cave, located in Piloña (in Asturias, northern Spain) has provided the best collection of Neanderthals that exists on the Iberian Peninsula. The team has recovered the remains of 13 individuals from the cave. The group consisted of seven adults (four women and three men), three teenagers and three younger children.

Previous studies have been carried out by a multidisciplinary team led by the paleoanthropologist Antonio Rosas (CSIC's National Museum of Natural Sciences), the geneticist Carles Lalueza-Fox (Institute of Evolutionary Biology, run by CSIC and the Pompeu Fabra University) and by the archaeologist Marco de la Rasilla (University of Oviedo).

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Going with the gut

A teeming community of microbes thrives in the colon, all ultimately feeding on our leftovers. These tens of trillions of individual organisms (similar in number to all the human cells in the human body) belong to many different species. Our microbial communities vary enormously from person to person, but there’s a lot of what Carmody calls “redundancy in function”: different microbes can play the same roles. “At a functional level, we’re more similar than we would appear to be when we just look at the different bugs that are present,” she says.

There are about 150 times as many independent genes in our microbiome as we have in our own bodies, which gives our microbes a vast metabolic range—much bigger than ours. They can perform a whole bunch of functions that we can’t, says Carmody, such as breaking down materials we can’t digest, including cellulose. That functional range “has driven really profound, but very visible changes in biodiversity across animals that are linked to diet,” says Carmody. For example, unlike humans and most other primates, who carry our microbiomes at the rear end of our intestinal tracts, ruminants like cows and sheep that eat cellulose-rich grasses and shrubs but do not manufacture cellulose-digesting enzymes have evolved to keep theirs at the beginning, in four-chambered stomachs. This arrangement allows microbes to first break down the cellulose, which then makes the nutritional contents of the plant cell more available to the animal.

Although we lack cows’ stomachs, we too benefit from gut microbes that digest cellulose and other nutrients that resist digestion in the small intestine. They break these down into short-chain fatty acids, which we can absorb in our colons and use for energy. However, short-chain fatty acids provide fewer calories than the carbohydrates and proteins from which they are derived, because some of the energy goes to fuel the microbes themselves. “Microbes help us salvage energy from food that would otherwise go undigested. So under dietary conditions where fewer nutrients are absorbed in the small intestine and more make it into the colon, you’ve got greater energy return in the colon, but not greater energy return overall, because you’ve lost the ability to have first dibs on that food,” says Carmody.

When we change what we feed our microbes by changing what we eat, that will change the entire microbial ecosystem. “From the microbial communities’ perspective, on the raw diet the microbial community in the colon is seeing a large influx of starch. On the cooked diet, it’s not really seeing much starch come in at all,” says Carmody. “And so on the raw diet, competition will favor microbes that are very good at processing and metabolizing that starch, causing them to proliferate in number at the expense of those who can’t really take advantage of that starch.”


Neanderthals and sapiens

The cost, in terms of energy, of anatomical growth of the modern brain is unusually high, especially during breastfeeding and during infancy, and this seems to require a slowing down of body growth. The growth and development of this juvenile Neanderthal matches the typical characteristics of human ontogeny, where there is a slow anatomical growth between weaning and puberty. This could compensate for the immense energy cost of developing such a large brain.

In fact, the skeleton and dentition of this Neanderthal present a physiology which is similar to that of a sapiens of the same age, except for the thorax area, which corresponds to a child between five and six years, in that it is less developed. “The growth of our Neanderthal child was not complete, probably due to energy saving”, explains CSIC researcher Antonio Rosas.

The only divergent aspect in the growth of both species is the moment of maturation of the vertebral column. In all hominids, the cartilaginous joints of the middle thoracic vertebrae and the atlas are the last to fuse, but in this Neanderthal, fusion occurred about two years later than in modern humans.

“The delay of this fusion in the vertebral column may indicate that Neanderthals had a decoupling of certain aspects in the transition from infancy to the juvenile phase. Although the implications are unknown, this feature could be related to the characteristic enlarged shape of the Neanderthal torso, or slower brain growth”, says Rosas.


Materials and Methods

Materials.

Our sampling strategy aimed to collect dental calculus from a minimum of two independent populations, each consisting of at least five individuals, for each host genus and modern human lifestyle group (excepting Alouatta) (SI Appendix, Table S1 and Dataset S1). Dental calculus was sampled from twentieth-century skeletal remains of wild Alouatta (A. palliata), Gorilla (G. berengei beringei G. berengei graueri G. gorilla gorilla), and Pan (P. troglodytes schweinfurthii P. troglodytes ellioti P. troglodytes verus) and from archaeological Neanderthals and modern humans using established protocols (DOIs: 10.17504/protocols.io.7vrhn56 and 10.17504/protocols.io.7hphj5n). Although many present-day human dental plaque datasets are publicly available, they have been shown to not be directly comparable to dental calculus (23), and consequently we generated dental calculus data for present-day humans. The study of deidentified present-day dental calculus was approved by the Institutional Review Board for Human Research Participant Protection at the University of Oklahoma (IRB no. 4543). All samples were collected under informed consent during routine dental cleaning procedures by practicing dental odontologists. For additional sample context descriptions and additional ethical approval information, reference SI Appendix, section S2.1.

Laboratory Methods.

For all museum and field station samples, we performed DNA extraction in dedicated cleanroom facilities using a protocol optimized for the recovery of degraded and fragmentary DNA (86). Present-day calculus was extracted as previously described (23). For all samples, DNA was built into dual-indexed Illumina libraries (87) and shotgun sequenced. In addition, a subset of samples were separately subjected to UDG treatment (88), followed by deep sequencing. Negative controls were included in all extraction and library construction batches. Sequencing was performed on either Illumina NextSeq. 500 or HiSeq. 4000 platforms. For details, reference SI Appendix, section S2.2–S2.4 and protocols.io under DOI: 10.17504/protocols.io.bq7wmzpe.

Data Processing and Quality Filtering.

For detailed descriptions of preprocessing and analysis procedures, including code, reference SI Appendix and external data repository (GitHub repository: https://github.com/jfy133/Hominid_Calculus_Microbiome_Evolution Archive DOI: 10.5281/zenodo.3740493). Additional ancient (13) and present-day dental calculus (23) data from previous studies were downloaded from the Online Ancient Genome Repository (OAGR) (https://www.oagr.org.au/) and the European Bioinformatics Institute (EBI) European Nucleotide Archive (ENA) (https://www.ebi.ac.uk/ena/) databases, respectively. Comparative metagenomes from present-day modern human microbiome and environmental sources were additionally downloaded from the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) database (https://www.ncbi.nlm.nih.gov/sra/). Accession numbers and download instructions for all FASTQ files are provided in SI Appendix, section S3.1. The EAGER pipeline (89) was used to perform initial preprocessing of sequencing data to remove possible modern human DNA sequences that can interfere with taxonomic profiling (due to present-day modern human DNA contamination in microbial reference genomes). We used relaxed bwa aln (90) mapping parameters for aDNA (−n 0.01), and nonhuman reads from replicate samples and libraries were then concatenated per individual. Human-mapped sequences were then poly-G clipped prior to reporting of mapping statistics. Processing statistics are provided in SI Appendix, section S3.2.

Taxonomic Binning and Preservation Assessment.

For taxonomic binning, we used the aDNA-optimized high-throughput aligner MALT (27, 91) together with the NCBI nt database (October 2017 uploaded to Zenodo under DOI: 10.5281/zenodo.4382154) and a custom NCBI RefSeq database (containing bacteria, archaea, and Homo sapiens, October 2018, SI Appendix, section S3.3) and employed a relaxed percent identity parameter of 85% and a base tail cut off (“minimum support”) of 0.01%. Resulting RMA6 files were loaded into MEGAN6 CE (64) and prokaryotic Operational Taxonomic Unit (OTU) tables were exported (Dataset S2). A comparison of the two databases is provided in SI Appendix, section S3.3. Given the challenges of low preservation and contamination in ancient microbiome studies, we performed a multistep procedure to screen for and remove poorly preserved samples and contaminant OTUs from the non-UDG-treated dataset (SI Appendix, Fig. S2). We developed a visualization for the identification of calculus samples with weak oral microbiome signatures (SI Appendix, Fig. S3). This procedure involves comparing identified taxa to their previously reported isolation source(s), ranking these taxa from most to least abundant, and tracking the cumulative percentage of oral taxa along this rank (termed here as “decay”). Samples with a low percentage of oral taxa after an initial “burn-in” based on stabilization of curve fluctuation were removed from downstream analysis. Reference SI Appendix, section S3.4 for details. We compared this method to results obtained using SourceTracker (28)—which was performed on 16S-mapped reads filtered from shotgun data using EAGER (with comparative present-day modern human and environmental metagenomes as sources), followed by closed-reference clustering using QIIME (92)—and found concordance between the two methods (SI Appendix, Fig. S3). We next used the R package decontam (29) to statistically detect putative laboratory and environmental contaminants (as present in negative controls and a set of archaeological bone samples—SI Appendix, section S3.6), which were then removed prior to downstream analysis. To authenticate the remaining OTUs, we utilized the output of MaltExtract (93) in the MaltExtract-Interactive Plotting App (MEx-IPA) tool (DOI: 10.5281/zenodo.3380011), which we developed for rapid visualization of characteristic aDNA patterns, such as cytosine to thymine deamination, short fragment lengths, and edit distance from reference (SI Appendix, Fig. S4 and section S3.5). After mapping with EAGER to well-known oral taxa, we also validated DNA damage patterns using DamageProfiler (Fig. 1C) (94).

Microbial Compositional Analysis.

To remove low-abundance environmental contaminants or spurious hits, we selected a minimum abundance cutoff of 0.07% of alignments for genus-level and 0.04% of alignments for species-level identifications (SI Appendix, Figs. S7 and S8 and section 5.2). We normalized profiles through phylogenetic isometric-log-ratio transformation (95) of the abundance-filtered OTU tables and then performed PCoA on the resulting euclidean distances (SI Appendix Fig. S5 C i D i SI Appendix, section S4.1). To statistically verify host genus clusters, we used the adonis function from the R package vegan to perform PERMANOVA (35) analysis after controlling from unequal sample sizes (SI Appendix, section S4.2). After removal of poorly preserved samples, oral communities show distinct centroids for each host genus (bootstrapped PERMANOVA, ɑ = 0.05, P = 0.001, pseudo-F = 5.23, R 2 = 0.28) Alouatta was excluded due to small sample size. We performed bootstrapped hierarchical clustering (96) on the euclidean distances of centered log ratio–transformed OTU tables and visualized the results in the form of a heatmap (Fig. 3 and SI Appendix section S4.3). Sample and taxon clustering was performed with the McQuitty hierarchical clustering algorithm, and taxon blocks within the heatmap were selected by visual inspection. Bootstrap values of sample clusters were estimated through the R package pvclust (96). Species oxygen-tolerance metadata was obtained from the BacDive database (97) via the BacDiveR R package (DOI: 10.5281/zenodo.1308060). For validation of the observations made on the heatmaps, we also performed grouped indicator analysis (98) (SI Appendix, section S4.4). Clustering of human oral microbiomes by variables such as time, geography, and dietary subsistence was assessed using PCoA, PERMANOVA, and hierarchical clustering (SI Appendix, section S4).

Core Microbiome Analysis.

Using the contaminant-filtered OTU tables of well-preserved samples, we converted all taxa above the minimum support threshold to a presence/absence profile. Taxa were required to be present in at least half (50%) of the members of a population for it to be considered core to the population and to be present in at least two-thirds (66%) of populations to be considered core to a host group (SI Appendix, Fig. S9 reference SI Appendix, section S5.2 for parameter experimentation details). We then generated UpSet plots (99) to visualize the microbial intersections of each host group at both the species and genus levels (Fig. 2 A i B), and we also compared the results between both databases. Further discussion on the exclusion of the common soil genus Mycobacterium from core genera is provided in SI Appendix, section S5.2. Validation of results through smaller sample sizes was carried out by bootstrapping analysis, which was performed by randomly subsampling (with replacement) individuals from each host genus and rerunning the core calculation procedure to 1,000 replicates (SI Appendix, section S5.3). We created a diagram of the core human oral microbiome (Fig. 2C) based on published fluorescence in situ hybridization (FISH) images of human dental plaque (8, 100). For species/genera that were not analyzed in these publications, literature searches were performed to find evidence of their localization within plaque based on immunohistochemistry, immunofluorescence, or FISH (SI Appendix, sections S5.1 and S5.4). All members of the human core microbiome are shown, including those also shared with other African hominids and howler monkeys. For further details, reference SI Appendix, section S5.3.

Genomic Analysis.

We used EAGER to map (see below for more details) the deep-sequenced UDG-treated dataset and four samples from present-day individuals (Alouatta, 3 Gorilla, 3 Pan, 4 Neanderthal, 3 ancient modern human, 6 present-day modern human, 4 total: 23) against the reference genomes of Tannerella forsythia i Porphyromonas gingivalis (SI Appendix, section S5.5). We used bedtools (101) to calculate the breadth and depth coverage of a set of known virulence factors for these two taxa. To reduce the risk of spurious alignments (e.g., from cross mapping of conserved sequences), we filtered out genes that had a breadth of coverage less than 70% and/or that appeared to have strongly different coverage depths compared to the rest of the genome (reference SI Appendix, section S5.5 for more details). The resulting genes were visualized as a heatmap for comparison (SI Appendix, Fig. S9). We selected all species-level Streptococcus alignments from the shallow sequenced dataset minimum support filtered NCBI nt–MALT OTU tables and assigned them to one of eight species groups based on the literature (67) (reference SI Appendix, section S5.6 for group definitions). We then calculated the fraction of alignments for each species group over all taxonomic alignments for each sample (Fig. 5B). To further validate the results, we calculated a similar ratio but based on the mapping of the deep-sequenced dataset against a superreference of 166 Streptococcus genomes (see below). We identified abpA- and abpB-like gene coordinates from the superreference using panX (102), then extracted the number of reads mapping to these annotations and calculated the fraction of these reads over all Streptococcus superreference mapped reads. We then applied a Mann–Whitney U test to test the null hypothesis of no difference between the distributions of ratios of Homo and nonhuman primates, as well as compared these results to a distribution of P values of 100 randomly shuffled group assignments (reference SI Appendix, section S5.7 for more details). Reference sequences of abpA i abpB were extracted from Streptococcus genomes in RefSeq and indexed for mapping. All shallow sequencing dataset samples were mapped against all reference strains. For samples with a gene coverage of at least 40% at 1×, a consensus sequence was exported from the Integrative Genome Viewer (IGV) (103). An input file of the consensus sequences and references was generated in BEAUTi and used to run BEAST2 (104) for Bayesian skyline plot analysis. For details, reference SI Appendix, section S5.9.

Microbial Phylogenetics.

We first attempted a competitive-mapping strategy against genus-wide superreferences of identified core taxa (reference SI Appendix, sections S6.1 and S6.2), but this approach yielded only limited results (SI Appendix Fig. S10 and section S6.3). We then instead performed phylogenetic reconstruction by mapping the same dataset to a single representative genome for each genus, considered as representing a population of related taxa. To account for challenges with low-coverage ancient data, we called SNPs using MultiVCFAnalyzer and required each SNP call to have a minimum of 2× coverage and a support of ≥70% of reads (SI Appendix, section S6.5). The resulting FASTA alignments were loaded into R. Samples with fewer than 1,000 SNPs were removed, and pairwise distances were calculated based on the JC69 model (105). A bootstrapped neighbor-joining algorithm from the R package ape (106) was applied to the distance matrices with 100 replicates (SI Appendix, section S6.6). Trees were visualized with ggtree (107). Finally, we retained trees where the basal internal nodes had bootstrap supports of ≥70% (SI Appendix, Fig. S11). The same procedure was then applied to the shallow sequencing dataset with the additional samples described above in the main text (SI Appendix, Fig. S12). To test whether pre-14 ka individuals clustered with Neanderthals due to reference bias, we calculated the median number of positions that were shared between EMN001 and Neanderthals to a histogram of median pairwise comparisons between all modern human individuals (SI Appendix, section S6.6).

Functional and Metabolic Pathway Analysis.

We took two approaches to characterizing the functional profiles of the calculus metagenomes. First, we used HUMANn2 (63) [with MetaPhlAn2 (108) generated taxonomic profiles] to generate functional profiles based on the UniRef90 (109) and ChocoPhlAn (July 2018) (63) databases. Preservation was independently assessed for pathway abundance and Kyoto Encyclopedia of Genes and Genomes (KEGG) ortholog functional profiles, SI Appendix, section S7.1. We compared the functional profiles of well-preserved calculus between host groups using pathway abundance (n = 94) and gene families converted to KEGG orthologs (n = 109) using PCA (SI Appendix, Fig. S13). Orthologs with the strongest loadings were visualized with biplots (SI Appendix, Fig. S13 AC), and the species from which these orthologs were derived were determined (SI Appendix, Fig. S13 BD). The clustering of host genera in PCAs using only orthologs in specific pathways (carbohydrates, amino acids, lipids) was also explored (SI Appendix, Fig. S10 AC). For details, reference SI Appendix, section S7.1.4. Second, we used AADDER (included within MEGAN6 CE) (64) to profile the number of alignments to annotations present in the custom RefSeq database as aligned by MALT (see above). We then used MEGAN6 to export SEED category (110) profiles. Preservation was independently assessed for SEED protein functional profiles, reference SI Appendix, section S7.2. We compared the functional profiles of well-preserved calculus (n = 95) between host groups using proteins but not higher-level pathways (SI Appendix, Fig. S13). The proteins with the strongest loadings were visualized using biplots (SI Appendix, Fig. S13 EG), and the species from which these proteins were derived were determined (SI Appendix, Fig. S13 FH). The clustering of host genera in PCAs using only proteins in specific pathways (carbohydrates, amino acids, lipids) was also explored (SI Appendix, Fig. S14 DF). For details, reference SI Appendix, section S7.2.3.


Pogledajte video: Neandertalac iz Kirgistana


Komentari:

  1. Trennen

    the Imaginary :)

  2. Tanak

    Pogodili ste cilj. Čini mi se da je to vrlo odlična misao. U potpunosti se slažem sa tobom.

  3. Sanris

    I can hardly believe that.

  4. Avalloc

    tvoje razmišljanje je veličanstveno



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