So what was it? Was the crazy old woman ranting about nothing?
With a sigh, Margo switched on the machine and sat back. She replaced the plant press and the incised disk in her carryall, brushing away a few packing fibers clinging to the press, packing fibers from the crate. There were additional traces inside her handbag. Yet another reason to clean the damn thing out.
The packing fibers.
Curious, she picked one up with the tweezers, laid it on a slide, and placed it under the stereo-zoom. It was long and irregular, like the fibrous vein of a tough-stemmed plant. Perhaps it had been pounded flat by Kothoga women for household uses. Through the microscope, she could see the individual cells gleaming dully, their nuclei brighter than the surrounding ectoplasm.
She thought back to Whittlesey’s journal. Hadn’t Whittlesey mentioned specimen jars being broken, and his need to repack the crate? So, in the area of the deserted hut, they must have thrown out the old packing material, which had become soaked in formaldehyde, and repacked the crate with material found lying near the abandoned hut. Fibers prepared by the Kothoga, perhaps; probably for weaving into coarse cloth or for the production of rope.
Could the fibers have been what the woman was referring to? It seemed impossible. And yet, Margo couldn’t help a little professional curiosity about it. Had the Kothoga actually cultivated the plant?
She plucked out a few fibers and dropped them in another mortar, added a few drops of enzyme, and ground them up. If she sequenced the DNA, she could use Kawakita’s program to at least identify the plant’s genus or family.
Soon, the centrifuged DNA from the fibers was ready for the electrophoresis machine. She followed her usual procedure, then switched on the current. Slowly, the dark bands began forming along the electrified gel.
A half hour later, the red light on the electrophoresis machine winked out. Margo removed the gel tray and began recording the position of the dots and bands of migrated nucleotides, typing her results into the computer.
She punched in the last position, instructed Kawakita’s program to search for matches with known organisms, directed the output to the printer, and waited. Finally, the pages began scrolling out.
At the top of the first sheet, the computer had printed:
Species: Unknown. 10% randomized genetic matches with known species.
Genus: Unknown
Family: Unknown
Order: Unknown
Class: Unknown
Phylum: Unknown
Kingdom: Unknown
Cripes, Margo! What did you put in here? I don’t even know if this is an animal or plant. And you won’t believe how much CPU time it took to figure that out!
Margo had to smile. So this was how Kawakita’s sophisticated experiment in artificial intelligence communicated with the outside world. And the results were ridiculous. Kingdom unknown? The damn program couldn’t even tell if it were a plant or an animal. Margo suddenly felt she knew why Kawakita had been reluctant to show her the program in the first place, why it took a call from Frock to get things in motion. Once you strayed out of its known provinces, the program grew flaky.
She scanned the printout. The computer had identified very few genes from the specimen. There were the usual ones common to almost all life: a few respiration cycle proteins, cytochrome Z, various other universal genes. And there were also some genes linked to cellulose, chlorophylls, and sugars, which Margo knew were specific plant genes.
At the waiting prompt, she typed:
How come you don’t even know if it is an animal or plant? I see lots of plant genes in here.
There was a pause.
Didn’t you notice the animal genes in there, too? Run the data through GenLab.
Good point, thought Margo. She dialed up GenLab on the modem and soon the familiar blue logo popped up on the screen. She uploaded the DNA data from the fibers and ran it against their botanical sub-bank. Same results: almost nothing. A few matches with common sugars and chlorophylls.
On an impulse she ran the DNA data through the entire databank.
There was a long pause, and then a flood of information filled the screen. Margo quickly hit a series of keys, instructing the terminal to capture the data. There were numerous matches with a variety of genes she had never heard of.
Logging off GenLab, she fed the data she’d captured into Kawakita’s program, instructing it to tell her what proteins the genes coded for.
A complicated list of the specific proteins created by each gene started to scroll down the screen.
Glycotetraglycine collagenoid
Suckno’s thyrotropic hormone, 2,6 adenosine ￡gram positive￡
1,2,3, oxytocin 4-monoxytocin supressin hormone
2,4 diglyceride diethylglobulin ring-alanine
Gammaglobulin A, x-y, left positive
Hypothalamic corticotropic hormone, left negative
1-1-1 sulphagen (2,3 murine) connective keratinoid, III-IV involution Hexagonal ambyloid reovirus protein coat
Reverse transcriptase enzyme